CN117979905A - Scanner and image reconstruction method - Google Patents

Abstract

The technology provided herein relates to dual energy CT scanners and associated image acquisition and reconstruction techniques that increase spatial and temporal resolution over conventional dual energy CT scanner designs. The dual energy filter at the source as disclosed herein includes alternating materials that attenuate the X-ray source to different levels, providing spectral separation. In this way, the object to be imaged by the X-ray beam is detected by both the low energy spectrum and the high energy spectrum. The X-ray spectrum at the source is divided along the detector channel direction (column direction).

Description

Scanner and image reconstruction method

Statement of related application

The present application claims priority from U.S. provisional patent application No. 63/224,460, filed on 7 months 22 of 2021, and U.S. provisional patent application No. 63/244,496, filed on 9 months 15 of 2021, which are incorporated herein by reference in their entireties for all purposes.

Technical Field

The technology provided herein relates to radiology and radiation therapy, and in particular, but not exclusively, to devices, methods and systems for medical imaging and image reconstruction.

Background

Medical imaging is used to diagnose, stage, plan treatments, guide treatments, and evaluate the patient's therapeutic response to various types of diseases, injuries, and other conditions. In particular, computed Tomography (CT) is a form of medical imaging that uses multiple two-dimensional X-ray measurements taken from different angles to produce a three-dimensional model of an object (e.g., a patient or portion thereof). CT imaging produces tomographic (sectional) images of a target region of a patient or portion thereof, allowing a user to image the interior of the patient without dissecting the patient. In conventional CT, the patient is placed horizontally on a table or gurney, and the patient and table are moved into a CT scanning apparatus. Alternatively, the gurney may be fixed and the CT scanner moved horizontally. New techniques are needed to allow a patient to be safely imaged in a variety of positions, e.g., vertical and/or substantially vertical positions (e.g., standing, sitting, kneeling, etc.) in addition to horizontal and/or substantially horizontal positions (e.g., lying (e.g., prone or supine)) and other patient positions, e.g., leaning forward or backward and other orthopedic positions. New techniques are also needed to allow image reconstruction for both single energy and simultaneous dual energy acquisitions of such CT scanners.

Disclosure of Invention

The technology described herein relates to medical imaging, such as Computed Tomography (CT), magnetic Resonance Imaging (MRI), positron Emission Tomography (PET), single Photon Emission Computed Tomography (SPECT), photon counting computed tomography, portal imaging (e.g., prior to treatment), radiographic localizer, topography, or scanning projection radiography ("scout view") (e.g., prior to imaging scanning and/or prior to treatment).

Dual Energy CT (DECT) can produce various patient images that are useful in clinical radiology as an alternative or supplement to single energy CT. For example, a dual energy CT scanner may produce a pair of images (X-ray attenuation map) at both low and high energies. In addition, dual energy CT scanners are capable of creating virtual monoenergetic, effective atomic number, electron density, material specific and virtual non-contrast images, as well as other image types, which can be used in both radiology and radiation therapy applications. For example, in radiation therapy, the effective atomic number and electron density images can be used to calculate the blocking capability of charged particles used in particle therapy. In this manner, proton blocking capability images can be used in a treatment planning system for proton beam therapy. In addition, in radiology, dual energy CT scanners provide valuable information for clinicians to diagnose lesions in the abdomen, kidneys, liver, and lungs. In addition, dual energy CT scanners facilitate the identification of materials for gout, calcium, and iodine contrast agents, as well as the separation of these materials from bone and other bodily materials. In some cases, a dual energy CT scanner may provide the same quality image as a single energy CT while reducing the patient dose. In short, dual energy CT scanners provide clinical benefits, for example, by providing more diagnostic information than single energy CT scanners for the same dose.

Conventional dual energy CT scanners utilize sequential scans separated in time by at least one rotation of the same subject at different kV levels. Variations of conventional dual energy CT include temporarily changing the X-ray source energy, using multiple X-ray tubes, using an energy resolving detector, and filtering the X-ray beam in the row direction at the detector or source. The quality of dual energy CT images depends inter alia on the spatial, temporal, contrast and energy resolution of the acquisition system and the reconstruction algorithm. Conventional dual energy CT scanners require improvements in spatial registration and temporal resolution of two images produced at two different energy spectrums. In particular, spectral separation of low energy acquisitions and high energy acquisitions is desirable so that higher contrast and material separation can be provided in the image. Some conventional dual energy CT scanners have drawbacks (e.g., poor temporal registration, susceptibility to motion artifacts, limited spectral separation, high noise on low kV images, and/or are expensive, slow, bulky, or subject to higher doses). For example, a system with multiple tubes may provide good spatial and temporal resolution, but with high cost and complexity.

The technology provided herein relates to dual energy CT scanners and associated image acquisition and reconstruction techniques that increase spatial and temporal resolution over conventional dual energy CT scanner designs. The dual energy filter at the source as disclosed herein includes alternating materials that attenuate the X-ray source to different levels, providing spectral separation. In this way, the object to be imaged by the X-ray beam is detected by both the low energy spectrum and the high energy spectrum. The X-ray spectrum at the source is divided along the detector channel direction (column direction). The two spectra pass through the object and are measured simultaneously, and the controller parses the low energy and high energy signals into a complete data set that can be reconstructed into two separate low energy and high energy images.

In one aspect, the present disclosure provides a Computed Tomography (CT) scanner comprising: a source positioned a first distance from the center, wherein the source is rotatable about the center; and a plurality of detectors rotatable about a center. The plurality of detectors are positioned at a plurality of distances from the source. In some embodiments, the center is an axis of rotation.

In some embodiments, each of the plurality of detectors is positioned a second distance from the center.

In some embodiments, the first distance is greater than the second distance.

In some embodiments, each of the plurality of detectors is oriented toward the source.

In some embodiments, each of the plurality of detectors includes a detector face defining an input plane, and wherein the input plane is orthogonal to an incident beam from the source.

In some embodiments, each of the plurality of detectors is oriented toward the center.

In some embodiments, each of the plurality of detectors is oriented such that an edge is aligned with an edge of an adjacent detector.

In some embodiments, the plurality of detectors define a field of view of at least 50 centimeters (e.g., 50, 55, 60, 65, 70, 75, 80, 85, 90 centimeters, etc.).

In some embodiments, the variance of photon fluence between the plurality of detectors is less than 50% (e.g., less than 50%, 45%, 40%, 35%, 30%, 25%, 20%, 15%, 10%, or 5%).

In some embodiments, the CT scanner is movable between an upright configuration, a tilted configuration, and a horizontal configuration.

In another aspect, the present disclosure provides a Computed Tomography (CT) scanner that includes a source and a filter defining an imaging plane. The filter includes a first filter portion having a first material and/or a shaping member, a second filter portion having a second material and/or a shaping member, and a third filter portion having the first material and the second material, which may also include a shaping member (e.g., a bow tie shaping member). The filter is movable relative to the source to align any of the first, second and third filter portions with the imaging plane.

In some embodiments, the third filter portion comprises alternating columns of the first material and the second material, wherein each column intersects the imaging plane.

In some embodiments, the first material attenuates the X-ray spectrum by a first amount; and the second material attenuates the X-ray spectrum by a second amount different from the first amount.

In some embodiments, the first material has a first mass attenuation coefficient in the range of 0.1cm ²/g to 200cm ²/g (e.g., 0.1, 0.5, 1, 5, 10, 50, 100, 150, 200) that corresponds to an excitation in the range of 10 to 200kVp (e.g., ,10、15、20、25、30、35、40、45、50、55、60、65、70、75、80、85、90、95、100、105、110、115、120、125、130、135、140、145、150、155、160、165、170、175、180、185、190、195、200)) and the second material has a second mass attenuation coefficient that is different from the first mass attenuation coefficient corresponding to the excitation.

In some embodiments, the third filter portion is located between the first filter portion and the second filter portion.

In some embodiments, the filter defines a radius.

In some embodiments, the filter adjustment assembly includes a motor, a frame, and a linkage coupled between the motor and the frame. In some embodiments, the filter is coupled to a frame.

In some embodiments, the first filter portion at least partially overlaps the third filter portion and the second filter portion at least partially overlaps the third filter portion.

In another aspect, the present disclosure provides a method of creating a CT image, the method comprising rotating a source and at least one detector about an axis. The at least one detector is configured to detect an output from the source. The method further includes recording the output signal from the at least one detector as sampled data, dividing the sampled data into a first data set and a second data set, complementing the first data set with a data complementing module to create a first complete data set, and complementing the second data set with a data complementing module to create a second complete data set. The method further includes reconstructing a first CT image using the complete first data set and reconstructing a second CT image using the complete second data set.

In some embodiments, the data complement module utilizes conjugated data.

In some embodiments, the data complement module utilizes high order interpolation.

In some embodiments, the data complement module utilizes a machine learning method.

In some embodiments, the method further comprises iterating the reconstructing the first CT image and/or the second CT image.

In some embodiments, the source and the at least one detector translate along the axis while rotating about the axis.

In some embodiments, the method further comprises transforming the first dataset from a first geometric reference frame to a second geometric reference frame.

Additional embodiments will be apparent to those skilled in the relevant art based on the teachings contained herein.

Drawings

These and other features, aspects, and advantages of the present technology will become better understood with reference to the following drawings. The patent or application document contains at least one drawing which is drawn in color. The patent office will provide copies of this patent or patent application publication with color drawings at the request and in the event of a necessary fee.

Fig. 1 is a front view of a multi-axis CT scanner.

Fig. 2 is a perspective view of the scanner of fig. 1 including a patient positioning assembly.

Fig. 3 is a bottom perspective cut-away view of the scanner of fig. 1.

Fig. 4 is a perspective view of a scanner ring assembly of the scanner of fig. 1.

Fig. 5 is a perspective view of a source collimator assembly of the scanner of fig. 1.

Fig. 6A is a perspective view of the source collimator assembly of fig. 5, shown with the filter in a first position (e.g., a bottom position).

Fig. 6B is a perspective view of the source collimator assembly of fig. 5, shown with the filter in a second position (e.g., a top position).

Fig. 7 is a top view of a source assembly oriented with respect to a conventional fan-beam detector assembly and with respect to a detector assembly according to embodiments disclosed herein.

Fig. 7B is a schematic diagram of various orientations of a plurality of detectors.

Fig. 8 is an enlarged view of the detector assembly illustrating each detector positioned the same distance from the axis of rotation and facing the source.

Fig. 9 is a schematic diagram of the geometric reference frame of various source-detector systems.

Fig. 10 is an enlarged view of a detector assembly illustrating the incidence of X-rays from a source onto a plurality of detectors with respect to a fixed radius arc, wherein the arc is not centered on the X-ray source.

FIG. 11 is a comparison of scanner annulus sizes for a conventional detector assembly and a detector assembly as disclosed herein.

Fig. 12 is a graph of the ratio of X-ray flux at the detector assembly disclosed herein to X-ray flux at a conventional fan-beam detector assembly for a given detector position delta.

Fig. 13 is a schematic diagram of various detector assembly geometries and related variables.

FIG. 14 is a graph of scanner field of view as a function of detector assembly angle.

15A-15B illustrate sinusoidal and binary weighting of data acquired by a detector assembly.

Fig. 16A illustrates three X-ray samples (A, B, C) with the source in a first position, where sample a is acquired at a high energy and samples B and C are acquired at a low energy.

Fig. 16B illustrates the conjugate ray of sample a as sample a', which was acquired at low energy, and with the source in the second position.

Fig. 16C illustrates the conjugate ray of sample B as sample B', which is acquired at high energy, and wherein the source is in a third position.

Fig. 16D illustrates the conjugate ray of sample C as sample C' which is acquired at high energy and with the source in the fourth position.

Fig. 17A is a sinusoidal plot of samples A, A ', B, B ', C, and C ' of fig. 16A-16D.

Fig. 17B is a sinogram of a low energy reconstruction including both natural and conjugated samples.

Fig. 17C is a sinogram of a high energy reconstruction including both natural and conjugated samples.

Fig. 18 is a perspective view of an assembly having a low energy filter, a radial dual energy filter, and a high energy filter.

Fig. 19 is a graph illustrating low energy and high energy X-ray spectra of the dual energy filter of fig. 18.

FIG. 20 is a schematic diagram of a source and detector assembly including dual energy filters, illustrating four low energy regions and four high energy regions oriented radially.

Fig. 21 is a sinogram of dual energy data acquired for a single revolution.

Fig. 22A is a sinogram of a low energy reconstruction including both natural and conjugated samples.

Fig. 22B is a sinogram of a high energy reconstruction including both natural and conjugated samples.

Fig. 23A is a low energy sinogram.

Fig. 23B is a high energy sinogram.

Fig. 23C is a dual energy sinogram.

FIG. 24 is a series of images, where (a-b) is a reference for simulation, (c-d) is a high energy and low energy acquisition reconstruction, and (e-h) is a dual energy acquisition reconstruction using conjugate data archiving.

Fig. 25A is a graph comparing a first order approximation of a fan beam sample with respect to an equal fan (isofan) detector angle.

FIG. 25B is a graph of the percent error of the linear approximation of FIG. 25A as a function of detector angle.

FIG. 25C is a graph of percent error of the linear approximation of FIG. 25A as a function of field of view.

Fig. 26A is a graph of uniform equal sector sampling.

Fig. 26B is a graph of uniform equifan samples rearranged (rebin) into a fan-beam geometry, shown overlapping with uniform fan-beam samples for reference.

Fig. 26C is a graph of uniform equifan samples rearranged into a parallel beam geometry, shown overlapping with uniform parallel beam samples for reference.

Fig. 27 is a high order interpolation data complement scheme.

Fig. 28 is a method of dual energy image reconstruction.

It will be understood that the figures are not necessarily drawn to scale and that objects in the figures are not necessarily drawn to scale relative to each other. The accompanying drawings are illustrations that are intended to provide a clear and easily understood depiction of the various embodiments of the apparatus, systems, and methods disclosed herein. Wherever possible, the same reference numbers will be used throughout the drawings to refer to the same or like parts. Furthermore, it should be appreciated that the figures are not intended to limit the scope of the present teachings in any way.

Detailed Description

The technology provided herein relates to medical imaging and in particular, but not exclusively, to apparatus, methods and systems for radiology (e.g., using computer tomography) and radiation therapy.

In the detailed description of the various embodiments, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the disclosed embodiments. However, it will be appreciated by one skilled in the art that the various embodiments may be practiced without or with such specific details. In other instances, structures and devices are shown in block diagram form. Moreover, those skilled in the art will readily appreciate that the specific sequences of presenting and executing the methods are illustrative, and that the sequences are contemplated to be varied and still remain within the spirit and scope of the various embodiments disclosed herein.

All documents and similar materials cited in this application, including but not limited to patents, patent applications, articles, books, treatises, and internet web pages, are expressly incorporated by reference in their entirety for any purpose. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the various embodiments described herein belong. Where a definition of a term in a incorporated reference appears to differ from that provided in the present teachings, the definition provided in the present teachings shall control. The section headings used herein are for organizational purposes only and are not to be construed as limiting the subject matter described in any way.

Definition of the definition

In order to facilitate an understanding of the present technology, a number of terms and expressions are defined below. Additional definitions are set forth throughout the detailed description.

Throughout the specification and claims, the following terms take the meanings explicitly associated herein, unless the context clearly dictates otherwise. The phrase "in one embodiment" as used herein does not necessarily refer to the same embodiment, although it may. Furthermore, the phrase "in another embodiment" as used herein does not necessarily refer to a different embodiment, although it may. Accordingly, as described below, various embodiments of the present invention may be readily combined without departing from the scope or spirit of the present invention.

In addition, as used herein, the term "or" is an inclusive "or" operator and is equivalent to the term "and/or" unless the context clearly indicates otherwise. The term "based on" is not exclusive and allows for being based on additional factors not described, unless the context clearly indicates otherwise. In addition, throughout the specification, the meaning of "a", "an", and "the" include plural references. The meaning of "in.

As used herein, the terms "about," "approximately," "substantially," and "substantially" are understood by those of ordinary skill in the art and will vary to some extent depending on the context in which they are used. If the use of these terms is not clear to one of ordinary skill in the art in the context of the use of these terms, "about" and "approximately" mean plus or minus less than or equal to 10% of the particular term, and "substantially" and "significantly" mean plus or minus greater than 10% of the particular term.

As used herein, the disclosure of a range includes disclosure of all values and further divided ranges within the entire range, including endpoints and subranges given for the range.

As used herein, the suffix "-free" refers to a technical embodiment that omits the feature of the basic root of the word to which the "-free" is attached. That is, the term "X-free" as used herein refers to "no X", where X is a feature of a technique omitted from the "X-free" technique. For example, a "no calcium" composition does not include calcium, and a "no mix" process does not include a mixing step, etc.

Although the terms "first," "second," "third," etc. may be used herein to describe various steps, elements, compositions, components, regions, layers and/or sections, these steps, elements, compositions, components, regions, layers and/or sections should not be limited by these terms unless otherwise indicated. These terms are used to distinguish one step, element, composition, component, region, layer, and/or section from another step, element, composition, component, region, layer, and/or section. Terms such as "first," "second," and other numerical terms when used herein do not imply a sequence or order unless clearly indicated by the context. Thus, a first step, element, composition, component, region, layer or section discussed herein could be termed a second step, element, composition, component, region, layer or section without departing from the technology.

As used herein, a "system" refers to a plurality of real and/or abstract components that operate together for a common purpose. In some embodiments, a "system" is an integrated collection of hardware and/or software components. In some embodiments, each component of the system interacts with and/or is associated with one or more other components. In some embodiments, a system refers to a combination of components and software for controlling, executing, and/or directing a method.

As used herein, the term "computed tomography" is abbreviated as "CT" and refers to both tomography and non-tomography. For example, the term "CT" refers to various forms of CT including, but not limited to, X-ray CT, positron Emission Tomography (PET), single Photon Emission Computed Tomography (SPECT), and photon counting computed tomography. In general, computed Tomography (CT) involves the use of an X-ray source and a detector that rotates around the patient and then reconstructs the images into different planes. The X-ray current used in CT describes the current flowing from the cathode to the anode, and is typically measured in milliamperes (mA).

As used herein, the term "structured as a verb" means that the identified element or component has a shape, size, arrangement, coupling, and/or configuration to perform the structure of the identified verb. For example, a member "configured to move" is movably coupled to another element and includes the element causing the member to move or the member is configured to move in response to other elements or components. Thus, as used herein, "structured to [ verb ]" means a structure rather than a function. Furthermore, as used herein, "structured as a verb" means that the identified element or component is intended and designed to perform the identified verb.

As used herein, the term "associated with" means that the elements are part of the same component and/or operate together or interact/interact with each other in some way. For example, an automobile has four tires and four hubcaps. While all of the elements are connected together as part of the automobile, it is understood that each hubcap is "associated" with a particular tire.

As used herein, the term "coupled" refers to two or more components secured together by any suitable means. Thus, in some embodiments, the expression "coupled to" two or more parts or components shall mean that the parts are directly or indirectly connected or operated together, such as through one or more intervening parts or components. As used herein, "directly coupled" means that two elements are in direct contact with each other. As used herein, "fixedly coupled" or "fixed" means that two components are coupled to move integrally while maintaining a constant orientation relative to each other. Thus, when two elements are coupled, all portions of the elements are coupled. However, the description of a particular portion of the first element (e.g., the axle first end connected to the first wheel) connected to the second element means that the particular portion of the first element is disposed closer to the second element than other portions of the first element. Furthermore, an object resting on another object held in place by gravity alone will not "couple" to the lower object unless the upper object is otherwise substantially held in place. That is, for example, a book on a table is not coupled thereto, but a book stuck on a table is coupled thereto.

As used herein, the term "removably coupled" or "temporarily coupled" refers to one component being coupled to another component in a substantially temporary manner. That is, the two components are coupled in such a manner that the joining or separating of the components is easy and does not damage the components. Thus, components that are "removably coupled" can be easily decoupled and re-coupled without causing damage to the components.

As used herein, the term "operatively coupled" means that a plurality of elements or components, each movable between a first position and a second position or a first configuration and a second configuration, are coupled such that when a first element moves from one position/configuration to another, a second element also moves between the positions/configurations. Note that a first element may be "operatively coupled" to another element, rather than vice versa.

As used herein, the term "rotatably coupled" refers to two or more components coupled in a manner that enables at least one component to rotate relative to another component.

As used herein, the term "translatably coupled" refers to two or more components coupled in a manner that enables at least one component to translate relative to another component.

As used herein, the term "temporarily disposed" refers to a first element or component resting on a second element or component in a manner that allows the first element/component to move without decoupling or otherwise manipulating the first element. For example, a book is simply placed on a table, e.g., the book is not glued or otherwise secured to the table, but is "temporarily placed" on the table.

As used herein, the term "corresponding" means that the two structural components are sized and shaped to be similar to each other and can be coupled with a minimum amount of friction. Thus, the size of the opening "corresponding to" a member is slightly larger than the member so that the member can pass through the opening with a minimum amount of friction. This definition may be modified if two components are to be "tightly" fitted together. In this case, the difference between the sizes of the parts is even smaller, so that the friction amount increases. The opening may even be slightly smaller than the part inserted into the opening if the element defining the opening and/or the part inserted into the opening are made of deformable or compressible material. With respect to surfaces, shapes and lines, two or more "corresponding" surfaces, shapes or lines generally have the same size, shape and contour.

As used herein, a "travel path" or "path" when used in conjunction with a moving element includes the space through which the element moves when in motion. Thus, any inherently moving element has a "travel path" or "path".

As used herein, the expression that two or more portions or components "engage" each other shall mean that the elements exert a force or bias on each other, either directly or through one or more intervening elements or components. Further, as used herein with respect to a moving component, the moving component may "engage" another element during movement from one position to another and/or may "engage" another element once in the described position. Thus, it should be understood that the statement "element a engages element B when element a is moved to element a first position" and "element a engages element B when element a is in element a first position" is an equivalent statement and means that element a engages element B when moved to element a first position and/or element a engages element B when in element a first position.

As used herein, the term "operatively engaged" refers to "engaged and moved". That is, when used with respect to a first component configured to move a movable or rotatable second component, "operatively engaged" means that the first component applies a force sufficient to cause the second component to move. For example, a screwdriver may be placed in contact with the screw. When no force is applied to the screwdriver, the screwdriver is simply "coupled" to the screw. If an axial force is applied to the screwdriver, the screwdriver will press against the screw and "engage" the screw. However, when a rotational force is applied to the screwdriver, the screwdriver "operatively engages" the screw and causes the screw to rotate. Further, for electronic components, "operatively engaged" means that one component controls the other component by a control signal or current.

As used herein, the term "number" shall mean one or an integer greater than one (e.g., a plurality).

As used herein, the term "[ x ] is the name of an element or program set in the phrase" [ x ] moving between its first and second positions or "[ y ] is configured to move between its first and second positions. Further, when [ x ] is an element or component that moves between multiple locations, the pronoun "it" represents "[ x ]", i.e., the named element or component preceding the pronoun "it".

As used herein, a "radial side/surface" of a circular or cylindrical body is a side/surface that extends around or about its center or a height line passing through its center. As used herein, an "axial side/surface" of a circular or cylindrical body is a side that extends in a plane that extends substantially perpendicular to a height line passing through the center. That is, generally, for cylindrical soup cans, the "radial sides/surfaces" are generally circular side walls, and the "axial sides/surfaces" are the top and bottom of the soup can.

As used herein, the term "patient" or "subject" refers to an organism to be subjected to various tests provided by the technology. The term "subject" includes animals, preferably mammals, including humans. In a preferred embodiment, the subject is a primate. In an even more preferred embodiment, the subject is a human. For example, the term "subject" or "patient" refers to an organism, including but not limited to humans and veterinary animals (dogs, cats, horses, pigs, cows, sheep, goats, etc.). In the context of the present technology, the term "subject" or "patient" generally refers to an individual, namely: it will be subjected to CT scan to diagnose disease or injury; and/or prepare for treatment.

As used herein, a "diagnostic" test includes detecting or identifying a disease state or condition in a subject, determining the likelihood that a subject will infect a given disease or condition, determining the likelihood that a subject suffering from a disease or condition will respond to treatment, determining the prognosis (or the likely progression or regression thereof) of a subject suffering from a disease or condition, and determining the effect of treatment on a subject suffering from a disease or condition. For example, the diagnosis may be used to detect the presence or likelihood of a subject having cancer, or the likelihood of such a subject responding favorably to a compound (e.g., a drug, such as a drug) or other treatment.

As used herein, the term "disorder" generally refers to a disease, disorder, injury, event, or change in health condition.

As used herein, the term "treating" or "treatment" with respect to a disorder refers to preventing the disorder, slowing the onset or rate of progression of the disorder, reducing the risk of developing the disorder, preventing or delaying the progression of symptoms associated with the disorder, reducing or ending symptoms associated with the disorder, producing complete or partial regression of the disorder, or some combination thereof. In some embodiments, "treating" includes exposing the patient or a portion thereof (e.g., tissue, organ, body part, or other localized region of the patient's body) to radiation (e.g., electromagnetic radiation, ionizing radiation).

The term "network" as used herein generally refers to any suitable electronic network, including, but not limited to, a wide area network ("WAN") (e.g., TCP/IP based network), a local area network ("LAN"), a neighborhood network ("NAN"), a home local area network ("HAN"), or a personal area network ("PAN") employing various communication protocols (e.g., wi-Fi, bluetooth, zigBee, etc.). In some embodiments, the network IS a cellular network, such as a global system for mobile communications ("GSM") network, a general packet radio service ("GPRS") network, an evolution data optimized ("EV-DO") network, an enhanced data rates for GSM evolution ("EDGE") network, a 3GSM network, a 4GSM network, a 5G new radio, a digital enhanced cordless telecommunications ("DECT") network, a digital AMPS ("IS-136/TDMA") network, or an integrated digital enhanced network ("iDEN") network, or the like.

The term "computer" as used herein generally includes a plurality of electrical and electronic components that provide power, operational control, and protection to the components and modules within the system. For example, a computer may include, among other things, a processing unit (e.g., a microprocessor, microcontroller, or other suitable programmable device), memory, an input unit, and an output unit. The processing unit may include, among other things, a control unit, an arithmetic logic unit ("ALC"), and a plurality of registers, and may be implemented using known computer architectures (e.g., modified Harvard architecture, von Neumann architecture, etc.). "microprocessor" or "processor" refers to one or more microprocessors that may be configured to communicate in a stand-alone and/or distributed environment, and may be configured to communicate with other processors through wired or wireless communication, wherein such one or more processors may be configured to operate on one or more processor-controlled devices, which may be similar or different devices.

The term "memory" as used herein generally refers to any memory storage device of a computer and is a non-transitory computer-readable medium. The memory may include, for example, a program storage area and a data storage area. The program storage area and the data storage area may comprise a combination of different types of memory, such as ROM, RAM (e.g., DRAM, SDRAM, etc.), EEPROM, flash memory, hard disk, SD card, or other suitable magnetic, optical, physical, or electronic storage device. The processing unit may be connected to a memory and execute software instructions that can be stored in a RAM of the memory (e.g., during execution), a ROM of the memory (e.g., on a generally permanent basis), or another non-transitory computer-readable medium, such as another memory or disk. "memory" may include one or more processor-readable and accessible memory elements and/or components that may be located within a processor-controlled device, external to a processor-controlled device, and accessible via a wired or wireless network. Software included in implementations of the methods disclosed herein may be stored in memory. Software includes, for example, firmware, one or more application programs, program data, filters, rules, one or more program modules, and other executable instructions. For example, a computer may be configured to retrieve and execute instructions, etc., associated with the processes and methods described herein from memory.

The term "conjugate" as used herein generally refers to a sample that has a reciprocal relationship with another sample. The conjugate sample may comprise a sample measured through the same cross section of the subject as another sample. In a preferred embodiment, a first sample is acquired with the source and detector in a first orientation and a conjugate sample is acquired with the source and detector in a second orientation that is a mirror image of the first orientation.

Description of the invention

The technology provided herein relates to a medical imaging device. Although described in some embodiments with respect to Computed Tomography (CT), the present techniques are not limited to use with CT and may be used with other medical imaging techniques, such as radiography, fluoroscopy, MRI, SPECT, PET, photon counting computed tomography, and portal imaging (e.g., prior to treatment) or scanning projection radiography. Computed Tomography (CT), and in particular computed tomography, is an imaging technique that generates a cross-sectional image of a patient by mathematically combining a plurality of X-ray images (projections) taken along a cross-sectional plane at a range of angles. In conventional CT, generating tomographic images involves providing a set of projections of a plurality over an angular range of at least 180 degrees and preferably 360 degrees around the patient. The patient is typically moved through a gantry that holds an X-ray source and an X-ray detector that rotate in unison relative about the patient to acquire each X-ray projection set either continuously (helical scan) during orbital motion or stepwise (step scan) between orbits to obtain X-ray projection sets that together describe adjacent sectional images of the tissue volume. Patient movement in conventional CT is provided by supporting a horizontal patient on a horizontally extending radio translucent table that moves through a gantry.

CT imaging of some patients may be preferably performed with the patient in an upright position (e.g., sitting, kneeling, standing, and/or reclined position (e.g., sitting and reclined, sitting and forward-leaning, standing and reclined, standing and forward-leaning, kneeling and forward-leaning or kneeling and backward-leaning)). For example, a lung cancer patient receiving chest radiation therapy may prefer to be in a standing position in order to avoid exacerbating the cough that often accompanies the therapy. Certain health conditions, such as vertebral fractures, may be more pronounced in a weight bearing standing position. Thus, a CT scanner that records CT scans of a patient in a vertical position would be beneficial for medical diagnosis and treatment. Furthermore, a CT scanner that can scan in multiple axes, for example, to scan patients in a vertical position, patients in a conventional horizontal position, and patients in other positions, would expand the use scenarios of CT scanners to address more diseases, injuries, and conditions, and increase the cost effectiveness of CT scanners.

As described herein, dual energy CT image acquisition is provided using a physical filter at the source that includes alternating material windows (e.g., gold (Au) and molybdenum (Mo)), which filters the X-ray energy spectrum along the detector channel direction (column direction). In other words, the two materials in the filter provide different energy spectra to inspect the object. The frequency of alternating low energy signals and high energy signals is a free parameter of the design disclosed herein. In other words, a design with N detector channels may alternate energy levels for every M channels, resulting in N/M filter windows. In some embodiments, the alternating windows are oriented radially.

Reconstruction of the two images from the alternating discontinuous signal measurements of the detector is provided by a data completion (data completion) module to provide a complete continuous signal for each energy level. As discussed further herein, in some embodiments, the data complement module includes a conjugate data population scheme, high order interpolation, and/or machine learning. The image is also formed by sparse iterative reconstruction using only the native discontinuous signal as input to the iterative reconstruction. The systems and methods described herein improve the spatial, temporal, and energy resolution of dual energy CT images.

Apparatus and method for controlling the operation of a device

In some embodiments, the present technology relates to multi-axis medical imaging devices. In some embodiments, the medical imaging device is a Computed Tomography (CT) device, a Magnetic Resonance Imaging (MRI) device, a Positron Emission Tomography (PET) device, a Single Photon Emission Computed Tomography (SPECT) device, a photon counting computed tomography device, or a portal imaging or scanning projection radiography device. Although the present technology is described with respect to exemplary embodiments in which the medical imaging device is a Computed Tomography (CT) device, the present technology is not limited to CT scanning devices, and embodiments should be understood to include other types of medical imaging devices, methods, and systems.

In some embodiments, for example, as shown in fig. 1, the present technology provides a multi-axis CT scanner 100 that includes a column (e.g., a first column 104A and/or a second column 104B). In some embodiments, the multi-axis CT scanner 100 is as described in U.S. provisional patent application No. 63/121304, filed 12/4/2020, which is incorporated herein by reference. In some embodiments, the support posts are mounted into the floor of the room in which the multi-axis CT scanner is located. Further, in some embodiments, the multi-axis CT scanner 100 includes a gantry 108 (e.g., a "U-shaped" gantry). In some embodiments, the mast 108 includes a first mast arm 112A and a second mast arm 112B. In some embodiments, the mast 108 rotates about an axis (e.g., axis 116) relative to the first and second struts 104A, 104B, e.g., the first and second mast arms 112A, 112B rotate about the axis 116 relative to the first and second struts 104A, 104B. As such, the CT scanner 100 may be movable between an upright configuration, a tilted configuration, and a horizontal configuration. In some embodiments, a motor (e.g., a motor configured to rotate the gantry 108 relative to the struts 104A, 104B), power supply lines, and/or communication cables are provided within one or both of the gantry arms 112A and/or 112B.

In some embodiments, for example, as shown in fig. 2, the present technology provides a multi-axis CT scanner. In some embodiments, the user uses a multi-axis CT scanner to obtain a CT scan of the patient. In some embodiments, the patient is positioned vertically. In some embodiments, the vertically positioned patient is positioned slightly tilted (e.g., within 20 degrees of vertical (e.g., within 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 degrees)) so that the patient can rest on the surface for support to provide enhanced securement of the patient and limit movement of the patient. In some embodiments, the patient is positioned using the patient positioning system 120, and the user operates the control unit. In some embodiments, the patient positioning system 120 is as described in International patent application publication No. WO 2019/056055 and U.S. patent application publication No. 2020/0268327, each of which is incorporated herein by reference.

Further, in some embodiments, as shown in fig. 3 and 4, the multi-axis CT scanner includes a scanner ring 124 (e.g., an annular housing that includes (e.g., encloses) the X-ray source and the at least one X-ray detector). In some embodiments, rotating the gantry 108 causes the scanner ring 124 to rotate about the axis 116 along an arc, e.g., to move it from a first position to a second position. In some embodiments, the first position of the scanner ring 124 allows the patient to enter and/or exit the patient positioning system 120. In some embodiments, the second position of the scanner ring 124 is a position for obtaining a CT scan of the patient. In some embodiments, the second position of the scanner ring 124 is above the patient's head.

In some embodiments, the scanner ring 124 includes sources and detectors for CT, MRI, PET, SPECT, photon counting computed tomography, or portal imaging. Thus, in some embodiments, the scanner ring includes a medical imaging source (e.g., electromagnetic radiation source, X-ray source, gamma ray source, radio wave source, photon source, proton source, positron source, gamma ray source (e.g., gamma rays from a positron source)) and a medical imaging detector (e.g., electromagnetic radiation detector, X-ray detector, photon detector, gamma ray detector), e.g., for one or more of these imaging modes.

Furthermore, in some embodiments, the scanner ring 124 is configured to translate along an axis that is substantially parallel to the first and second gantry arms 102A, 102B, e.g., along an axis 128 as shown in fig. 1. In some embodiments, the scanner ring translates along a vertical (e.g., substantially and/or substantially vertical) axis, e.g., to obtain a CT scan of the patient in a vertical position. In some embodiments, the scanner ring translates along a horizontal (e.g., substantially and/or substantially horizontal) axis, e.g., to obtain a CT scan of the patient in a horizontal position.

In some embodiments, the scanner ring 124 includes (e.g., encloses) an X-ray generator that moves within the scanner ring 124 and thus rotates about the patient. In some embodiments, the scanner ring 124 includes (e.g., encloses) one or more X-ray detectors. In some embodiments, the X-ray generator generates a fan beam of X-rays in a plane extending through the scanner ring.

In some embodiments, the X-ray detector comprises an arcuate detector array in the plane. In some embodiments, a plurality of stationary X-ray detectors are positioned around the perimeter of the scanner ring 124 such that the X-ray detectors are always on the opposite side of the X-ray source that moves within the scanner ring 124. In some embodiments, the scanner ring 124 includes a moving X-ray detector that moves within the scanner ring 124 and is positioned opposite the moving X-ray generator, e.g., the X-ray generator and the X-ray detector move in unison such that the X-ray generator and the X-ray detector are on opposite sides of the scanner ring 124. In some embodiments, the scanner ring 124 is translated into position and stationary while the X-ray generator and X-ray detector move around the perimeter of the scanner ring 124. In some embodiments, the scanner ring 124 translates one or more times and/or continuously as the X-ray generator and X-ray detector move around the perimeter of the scanner ring 124 (e.g., to provide a helical scan). In some embodiments, the multi-axis CT scanner includes a slip ring (fig. 4) to transfer electrical power from the scanner ring 124 to the X-ray generator and the X-ray detector and to transfer communication signals between the scanner ring 124 and the X-ray generator and the X-ray detector.

In conventional fan-beam ("fanbeam") CT, the X-rays used to acquire the projections are collimated into a thin fan-beam lying in the cross-sectional plane and received by a narrow linear detector. The plurality of detectors in a conventional fan beam arrangement 150, such as that shown in fig. 7, are oriented toward the X-ray source 154 and centered on the X-ray source 154. In other words, in the conventional fan beam arrangement 150, each detector is positioned at the same or substantially similar distance from the X-ray source 154. In a conventional parallel CT arrangement, the X-ray source is a series of parallel rays, and the plurality of detectors are positioned at the same or substantially similar distance from the X-ray source.

Referring to fig. 7, ct scanner 100 includes an equifan arrangement 152 ("equifan detector source arrangement") positioned within scanner ring 124. The X-ray source 154 provides a fine fan beam lying in a plane 156 (fig. 5). The X-ray source 154 is positioned a first distance D1 from the center 158. In some embodiments, the source 154 may be rotatable about a center 158. The isocandela detector arrangement 152 also includes a plurality of detectors facing the source 154 and rotatable about a center 158. In the illustrated embodiment, the plurality of detectors 152 are positioned at different distances from the source 154. In other words, the plurality of detectors 152 are not positioned a constant distance from the source. In the illustrated embodiment, each of the plurality of detectors 152 is positioned a second distance D2 from the center 158. In other words, the second distance D2 (detector-to-center distance) is the same or substantially the same. In the illustrated embodiment, the first distance D1 (source-to-center distance) is greater than the second distance D2 (detector-to-center distance).

Referring to fig. 8, each of the plurality of detectors 152 is oriented toward the source (see source arrow 160) and centered on the axis of rotation (gray radial line 162). In other words, the flat face of each detector module is oriented towards the source, but the modules are located on the same radius from the center of rotation. Each of the plurality of detectors 152 includes a detector face 166 defining an input plane. In the illustrated embodiment, the input plane is orthogonal to the input beam 160 from the source.

Referring to fig. 9, a comparison of an equal sector arrangement with a conventional fan beam arrangement and a conventional parallel arrangement is illustrated. In other words, fig. 9 illustrates three geometry systems for X-ray sampling in a source-detector system. The physically acquired detector samples in the isochrone arrangement may be transformed (rearranged) into other geometric configurations, as further explained herein.

Referring to fig. 10, a small correction step is performed to resample each flat detector module to a detector arc 170 having an equal radius from the center of rotation. In other words, there is a small distance to be corrected between the constant radius arc 170 and the detector surface 166. Referring to fig. 7B, in some embodiments, detector 152A is oriented toward center 158 and/or some detector 152B is oriented toward source 154. In some embodiments, each of the plurality of detectors 152 is oriented such that the edge is aligned with the edge of an adjacent detector.

Referring to fig. 11, the iso-fan arrangement allows for a tighter and smaller design of the CT scanner ring when compared to a conventional fan-beam arrangement. In the illustrated embodiment, the CT scanner ring includes a bore having an inner diameter of approximately 85 cm. For an equifan arrangement, the plurality of detectors ("equifan detectors") fit within a CT ring having a thickness of about 33.5 cm. In contrast to an equivalent fan beam arrangement, the CT ring is about 50.7cm to fit multiple detectors ("fan beam detectors") that collimate the same X-ray beam width. In other words, the equifan arrangement reduces the size of the CT ring by about 34% compared to conventional fan beam arrangements. FIG. 11 illustrates the thickness difference of the CT annulus for a conventional fan beam arrangement and an equal fan arrangement, both of which have 85cm holes.

Referring to fig. 13, various data acquisition and image reconstruction variables in three geometry systems (fig. 9) as used herein are illustrated. Additional details of the variables shown in FIG. 13 are set forth in Table 1.

For simplicity of the following derivation and explanation, it is assumed that the speed of rotation of the tube is constant. Therefore, the source rotation angle is proportional to time, i.e., β+_t and θ+_t. However, in other embodiments, the scanner operates at a variable tube rotational speed.

Referring to fig. 12, the isocameter detector arrangement also has the benefit of increasing the flux at the detector. The geometric attenuation of X-rays follows an inverse square relationship (flux, Φ. Alpha. 1/r ²). As such, by bringing the detector closer to the source than in conventional fan beam geometries, flux attenuation is less (i.e., higher flux reaches the isocameter detector). The relationship between the flux reaching the isochrone detector (Φ _iso) and the flux reaching the conventional fan-beam detector (Φ _fan) is provided by the ratio of equation 1.

Equation 1

This ratio is plotted in FIG. 12 for the values of R and D and the range of-70.ltoreq.delta.ltoreq.70 for one example. In some embodiments, the variance of photon fluence between the plurality of detectors is less than 50%.

Referring to fig. 14, the scan field of view (FOV, also known as field of view) of an equi-sector detector arrangement is illustrated according to the full width of equi-sector angle 2δ _m. In some embodiments, the field of view is about 75cm. In some embodiments, the plurality of detectors define a field of view of at least about 50 cm.

Referring to fig. 6A, 6B and 18, the ct scanner 100 includes a filter 200. The filter 200 is located at or near the X-ray source 154. In other words, the filter 200 is positioned closer to the source 154 than either of the detectors 152. As described elsewhere herein, the source 154 emits a spectrum in an imaging plane 156 (fig. 5).

In the illustrated embodiment, the filter 200 is a dual energy filter. The filter 200 includes a first filter portion 204 comprising a first material, a second filter portion 208 comprising a second material, and a third filter portion 212 comprising the first material and the second material. In the illustrated embodiment, the third filter portion 212 is located between the first filter portion 204 and the second filter portion 208 and includes alternating columns of first material and second material (alternating windows of first and second material) that intersect the imaging plane 156. In some embodiments, the first filter portion at least partially overlaps the third filter portion, and the second filter portion at least partially overlaps the third filter portion (there is an overlapping transition between the filter portions). In the illustrated embodiment, the filter 200 is arcuate and defines a fixed radius. In other embodiments, the filter defines a variable radius. In other embodiments, the filter is planar and does not bend. In some embodiments, the filter includes five or more different portions of different materials. In some embodiments, the filter includes an air portion. In other embodiments, the filter comprises an aluminum filter or bow tie profile portion.

In some embodiments, the first material attenuates the X-ray spectrum by a first amount and the second material attenuates the X-ray spectrum by a second amount different from the first amount. For example, the first material may provide a low energy spectrum and the second material may provide a high energy spectrum. In other words, the two materials have different mass attenuation coefficients (which depend on both density and atomic number) such that different outgoing photon spectra with separate average energies are used to inspect the object. For example, an original spectrum of 140kVp photons (energy 0-140 keV) passing through the first material or the second material will produce a different emission spectrum. The first order measurement of each spectrum is the average photon energy per spectrum. Thus, the first material will produce a photon spectrum having an average energy E _a to detect an object, and the second material will produce a photon spectrum having an average energy E _b to detect an object. It may be advantageous to have E _a and E _b be far apart.

In some embodiments, the first material has a first mass attenuation coefficient in the range of 0.1cm ²/g to 200cm ²/g (e.g., 0.1, 0.5, 1,5, 10, 50, 100, 150, 200) that corresponds to an excitation in the range of 10 to 200kVp (e.g., ,10、15、20、25、30、35、40、45、50、55、60、65、70、75、80、85、90、95、100、105、110、115、120、125、130、135、140、145、150、155、160、165、170、175、180、185、190、195、200)) and the second material has a second mass attenuation coefficient for the excitation that is different than the first mass attenuation coefficient.

In some embodiments, the first material is gold (Au). In some embodiments, the second material is molybdenum (Mo). In some embodiments, the second material is tin (Sn).

Referring to fig. 19, an X-ray spectrum of a low energy first filter portion and a high energy second filter portion is illustrated. Each spectrum was normalized using a 150kVp unfiltered spectrum with the left vertical axis being the maximum and the right vertical axis being the unit area. In some embodiments, the high energy range and the low energy range are separated by an energy cutoff. In some embodiments, the energy cutoff is about 80kV. In other embodiments, the energy cutoff is in the range of about 60kV and about 100 kV.

Referring to fig. 6A and 6b, a CT scanner includes a filter adjustment assembly 300 positioned within a CT scanner ring. The filter adjustment assembly 300 includes a motor 304, a frame 308, and a linkage 312 coupled between the motor 304 and the frame 308. In the illustrated embodiment, the dual energy filter 200 is coupled to a frame 308. As such, the filter 200 may be moved relative to the X-ray source to align any of the first filter portion 204, the second filter portion 208, and the third filter portion 212 with the imaging plane. In other words, the filter adjustment assembly 300 translates the filter 200 relative to the source in order to align the desired filter portion with the X-ray beam. Fig. 6A illustrates the filter 200 in a first position (e.g., bottom position), and fig. 6B illustrates the filter 200 in a second position (e.g., top position).

Single energy scan reconstruction

For acquisition at a single energy, CT image reconstruction of a CT scanner is provided by acquiring raw acquisition data in an isosceles fan arrangement (isosceles fan geometry) and applying direct analytical reconstruction of isosceles fan rays. This requires transforming the variables of the equations of the parallel beam (Kak) or fan-beam filtered back projection (Feldkamp) reconstruction and performing steps similar to those of the reconstruction (e.g., weighting the data for geometric correction, filtering, and back projection) unless the exact parameters in these steps are determined by the transformation of the variables. See Kale,A.C.,Principles of Computerized Tomographic Imaging,2001;Feldkamp,L.A.,Practical Cone-Beam Algorithm,Journal of the Optical Society of America,1984;1：612-619.

Alternatively, CT image reconstruction is provided by taking the raw acquisition data in an equi-sector geometry and rebinning (transforming) the equi-sector data to a fan-beam geometry reference frame. Rearranging the equal sector sample data into a fan beam geometry is provided by equation 2:

equation 2:

With rearranged fan beam data, conventional fan beam reconstruction algorithms may be utilized. Alternatively, the fan beam data may again be rearranged into a parallel beam geometry, and a conventional parallel beam reconstruction algorithm may be used. Rearranging fan beam data into parallel beam geometry is provided by equation 3:

equation 3:

θ＝β+γ

ρ＝Rsinγ

It is worth noting that the use of conventional fan beam or parallel beam reconstruction algorithms on sampled data with equal fan geometry does not have a significant impact on reconstruction accuracy. This is because the rebinning from equi-fan to fan-beam is very close to linear conversion throughout the reconstructed field of view (FOV). The first order approximation of equation 2 is shown in equation 4.

Equation 4:

Both equations 2 and 4 are plotted in fig. 25A. The percentage error (% error) of the linear approximation (equation 4) plotted in fig. 25B, 25C from the complete equi-sector angle or equivalent reconstructed field of view is less than 3% for the entire field of view. In other words, FIGS. 25A-25C illustrate the gamma-delta relationship and its first order approximation given by equations 2 and 3.

26A-26C, the effect of the near linear rearrangement scheme is illustrated. The primary isosceles fan-shaped samples (fig. 26A) are rearranged into a fan-beam space (fig. 26B) and a parallel space (fig. 26C), and compared with samples taken primary in the respective fan-beam and parallel spaces. In other words, uniform sampling in the equal sector space (δ=nΔδ) (fig. 26A) is rearranged to auxiliary spaces in the fan-beam geometry (fig. 26B) and parallel-beam geometry (fig. 26C). For comparison, uniform sampling in each auxiliary space (fan beam, γ=nΔγ)) (parallel, ρ=nΔρ) is shown with rearranged equifan samples. As shown in fig. 26B, the rearranged equifan samples are nearly identical to the directly acquired fan beam samples.

One advantage of the isochrone arrangement is that it has improved image noise performance compared to the fan beam acquisition geometry due to the higher photon flux to the detectors on the edges, as they are physically located closer to the X-ray source in the isochrone compared to the fan beam. See, for example, fig. 12.

Dual energy scan reconstruction

To reconstruct a CT image with limited view artifacts, the Tuy data sufficiency condition of CT specifies the minimum angular scan range required. See Tuy HK.an inversion formula for cone-beam reconstruction.SIAM J Appl Math.1983;43:546-52. for a conventional fan beam CT acquisition, the data sufficiency condition is 180 ° +2γ _m, where 2γ _m is the full fan angle. For a fan angle of 2γ _m =60° (the approximate angle of a conventional system), this minimum scan range is thus 240 °. Thus, a complete data set of a single image reconstruction can be obtained with a 240 scan.

However, obtaining two complete data sets does not require a double minimum scan range (e.g., 480 °). In other words, a 360 ° fan beam acquisition contains two complete data sets that meet a 240 ° minimum. Referring to fig. 15b, two trapezoidal sampling regions, one black and one white, in 360 sinogram space illustrate two complete data sets. Geometrically, trapezoids are conjugate to each other, which means that each X-ray sample s (γ, β) is measured exactly twice. Thus, for a 360 scan, exactly two sets of redundant data are available for reconstruction.

As an example, the conjugate sample s ₂＝s(γ₂,β₂) of sample s ₁＝s(γ₁,β₁) in fan-beam space is given by equations 5-6 below:

Equations 5-6:

note that without loss of generality, we define s ₂ to sample at a time later than s ₁, and there is β ₂>β₁ due to β c t at constant tube speed. For reconstructing an image, weights w ₁ and w ₂ are used for two X-ray samples conjugated to each other. The sample s ^* to be used for reconstruction is calculated as in equation 7:

equation 7:

s^*＝w₁·s₁+w₂·s₂

practical reconstruction theory requires weights that w ₁,w₂ be greater than or equal to 0 and w ₁+w₂ =1. For single energy CT scans with scan ranges greater than 180 ° + fan angles and less than 360 °, the weights w ₁,w₂ are typically determined using a variety of methods, including the method of Parker (i.e., sinusoidal weights shown in fig. 15A) or Crawford and King. See Parker,D L,Optimal short scan convolution reconstruction for fanbeam CT,Medical Physics,1982;9：254-257. also Crawford,C R and King,K F,Computed tomograph scanning with simultaneous patient translation,American Association of Physicists in Medicine,1990;17：967-982.

For dual energy scanning using the proposed method described herein, low Energy (LE) and High Energy (HE) images can be reconstructed by utilizing conjugation. Referring to fig. 20-21, each X-ray sample is sampled twice in a single revolution, but since the energy regions alternate along the detector channel, each sample is acquired once using LE spectrum and once using HE spectrum. However, a proper artifact-free reconstruction requires that each X-ray view consists of samples from the same energy spectrum. Assuming s ₁＝s(γ₁,β₁) is an HE sample, s ₂＝s(γ₂,β₂)＝s(-γ₁,β₁+π+2γ₁) will be an LE sample, and the LE and HE datasets at points in sinogram space (γ ₁,β₁) can be formed using binary weights, see equation 8:

Equation 8:

s^LE(γ₁,β₁)＝0·s₁+1·s₂

Thus, for a view at β ₁, the missing low-energy data is filled in with the corresponding low-energy data from its conjugated view in a later scan. Similarly, the missing high energy data in view β ₂ is filled in with conjugated high energy data from earlier views:

s^HE(γ₂,β₂)＝1·s₁+0·s₂

Referring to fig. 16A-16D, simplified examples of conjugated X-rays in a dual energy scanning system are illustrated. In fig. 16A, three X-ray samples A, B and C are acquired. Sample a was collected at high energy (dark gray area) and samples B and C were collected at low energy (light gray area). FIGS. 16B, 16C and 16D illustrate conjugate rays for each sample. Referring to fig. 16B, the conjugate ray of the sample a is the sample a', which is acquired at low energy. In this way, the same object data is measured on the X-ray path corresponding to a or a', next at a high energy and next at a low energy. Similarly, referring to fig. 16C and 16D, paths B and B 'and C' are conjugate pairs, where one sample is measured at each energy level.

In some embodiments, the data complement module utilizes data conjugation (data conjugacy). 17A-17C, conjugation can be used to complement the data set required at each energy level of the image reconstruction. In other words, fig. 17-17C illustrate the concept of conjugate data complement with a simplified dual energy case having only two energy windows. Fig. 17A illustrates the locations in sinogram space where samples A, B and C and their corresponding conjugate pairs a ', B ' and C ' are taken. For low energy image reconstruction, the block of data containing sample a may be replaced with conjugate data from the region containing sample a'. As such, fig. 17B forms, and has one complete data set (raw samples B and C and conjugate sample a') that can be used to reconstruct a low energy image. Similarly, in fig. 17C, the conjugate block containing samples B 'and C' from fig. 17A is used to complement the data sets (raw sample a and conjugate samples B 'and C') required for high energy image reconstruction.

Referring to fig. 20-21, the simplified examples of fig. 16A-16D are extended to dual energy sources having multiple alternating low energy and high energy windows in the detector direction. In other words, a dual energy acquisition with equal sector detector geometry at a single projection view (i.e., at angle β) is illustrated in fig. 20. The dual energy filter is located at or near the source, producing low energy and high energy data that alternate in the detector channel direction (delta axis). In some embodiments, the dual energy filter is positioned closer to the source than the opposing detector. A sinogram representation (Cartesian coordinates) of dual energy data acquired for a single revolution (0. Ltoreq.beta. Ltoreq.2π) is illustrated in FIG. 21. Specifically, for each X-ray projection below the real dividing line at β=pi-2 δ, there is a conjugated X-ray above that line. For example, lines of a similar dashed type (e.g., thick dashed line, thin dashed line) in fig. 21 are conjugate samples. Similar to the process described in fig. 17A-17C, fig. 22A and 22B illustrate a data archiving (DATA FILING) scheme using the conjugated X-ray principle for low energy data and high energy data. The solid shaded areas are physically collected low and high energy data, while the pattern or hashed (hashed) areas are physically collected data sampled at a later viewing angle.

Using the reconstruction methods described herein, dual energy scanning can reconstruct low energy images and high energy images by utilizing the conjugates shown in fig. 21, 22A, and 22B. In some embodiments, the time resolution of the conjugated data archiving scheme is proportional to β ₂-β₁＝π+2γ₁.

In some embodiments, the data complement module utilizes high order interpolation to fill in data across detector channel blocks corresponding to other energies. Referring to fig. 27, an embodiment of high order interpolation is illustrated for signals complementing low energy and high energy datasets. Successive identical energy signals are formed in a given projection view by interpolation of the weighting scheme of the data across the detector columns. The temporally displaced projection views (e.g., 1 sample late, 1 sample early) have increased errors that are proportional to both the time difference and the distance from the isocenter.

In some embodiments, the data complement module utilizes machine learning to provide interpolation across energy slots within a given view. Each detector channel block encodes information about attenuation coefficients of different energies, thereby enabling a continuous same energy signal to be obtained.

In some embodiments, machine learning includes Convolutional Neural Network (CNN), U-Net architecture, and/or generating an antagonism network (GAN). For example, the machine learning network may use a T (β sample number) x U (δ or γ sample number) x V (detector row number) sinogram image (acquired locally) as input and output two tx U/2x V sinograms for each energy level. These two sinograms are then passed to an image reconstruction algorithm to produce two N (number of image pixels on x or y) x Nx M (number of image pixels on z) image volumes.

The machine learning network that learns interpolation is a network (original to original correction network) with the same input and output dimensions. This is in contrast to networks that directly learn how to reconstruct images, which are networks that employ sinogram inputs (T x U x V) and output two N x M images. In other embodiments, the machine learning network includes an image-to-image network in which the raw data is reconstructed once, and then a single nxn M image is passed to a convolutional neural network and one or two nxn M images are output. The image-to-image network may be used as an artifact correction method.

In some embodiments, the data complement module utilizes an Iterative Reconstruction (IR) algorithm. In some embodiments, iterative reconstruction algorithms based on sparse sampling (e.g., compressed sensing) may also use native discontinuous signal measurements within each view without having to perform data complement on the continuous signal. Thus, using only the raw data as input, low energy and high energy images can be obtained using an iterative reconstruction algorithm; thereby achieving the highest theoretically possible spatial and temporal resolution between the images.

In some embodiments, the data complement module utilizes any of data conjugation, higher order interpolation, machine learning, and/or iterative reconstruction to increase the resolution of the dual energy CT image. In some embodiments, the data complement module utilizes any combination of data conjugation, higher order interpolation, machine learning, and iterative reconstruction.

Each reconstruction scheme mentioned herein is applicable to helical acquisition. In some embodiments, the X-ray source translates along the axis of rotation (z-axis) relative to a stationary subject or patient. Thus, samples in the conjugate or higher order interpolation data completion module have a z-dependence associated therewith. As such, data inconsistencies associated with the z-correlation for data complement purposes may lead to image artifacts. The severity of these artifacts increases with increasing X-ray source translational speed (i.e., increasing pitch, increasing z-direction speed). However, below the threshold speed, the presence of these artifacts is insufficient to adversely affect image quality. In some embodiments, the threshold speed is a function of the end use of the imaging (e.g., treatment planning diagnostic radiology, etc.). In some embodiments, various artifact correction methods are utilized to increase the threshold speed. For example, image-to-image machine learning networks are utilized in some embodiments to correct artifacts.

Conventional CT image reconstruction algorithms are based on two basic assumptions: 1) The object remains the same throughout the scan; and 2) there is a set of consecutive object measurements in each view. Conventional CT hardware components are designed based on these two assumptions.

In single energy data acquisition, the CT scanner satisfies both assumptions. The first assumption is satisfied (assuming no object motion) and the material properties (e.g., photon attenuation coefficients) of the object are the same for a given energy probe. The second assumption is also satisfied by having a set of consecutive detectors to measure the signal opposite the X-ray source.

In dual energy data acquisition, conventional scanners are designed to meet these two basic assumptions. In particular, conventional dual energy CT hardware has a continuous signal in each view, as the detector channels of a given view are probed with the same energy spectrum. In contrast, the CT scanner 100 has alternating signals of low energy and high energy along the detector channel dimension, which is contrary to the second basic assumption. The low energy and high energy signals in any given projection view are no longer continuous. As set forth herein, the described systems and methods provide algorithmic correction to obtain continuous signals (or directly use discontinuous signals) in each view for dual energy image reconstruction.

23A-23C, simulations of CT acquisitions in the form of sinograms of low energy (FIG. 23A), high energy (FIG. 23B) and dual energy (FIG. 23C) are illustrated. The dual energy CT acquisition has alternating electromagnetic spectrum attenuation along the detector channel direction. In the simulation shown, the dual energy filter comprises 17 low energy bands (windows or columns) and 17 high energy bands (windows or columns), i.e. a total of 34 alternating bands.

Referring to fig. 24, image reconstruction of a simulated CT sinogram in accordance with fig. 23A-23C is illustrated. Fig. 24 (a) illustrates a high energy (e.g., 85 kV) reference for simulation, and fig. 24 (b) illustrates a low energy (e.g., 65 kV) reference. Fig. 24 (c) illustrates a high energy single energy acquisition reconstruction, and fig. 24 (d) illustrates a low energy single energy acquisition reconstruction. Fig. 24 (e) illustrates an uncorrected high energy image for dual energy acquisition utilizing the conjugated data archiving scheme described herein. Likewise, fig. 24 (f) illustrates an uncorrected low-energy image acquired with dual energies of the conjugate data archiving scheme described herein. Fig. 24 (g) and 24 (h) are corrected versions of fig. 24 (e) and 24 (f), respectively (e.g., with artifacts removed). In some embodiments, the artifacts are removed by smoothing the binary weights depicted in fig. 15B. For example, in some embodiments, the smoothed binary weights comprise gaussian filters on fig. 15B. In other words, the hard edges in fig. 15B result in image streaks seen in fig. 24 (e) and 24 (f). The systems and methods described herein provide several advantages. One advantage is that the detector array is centered on the axis of rotation while facing the focus, which provides a wide fan angle. In some embodiments, the field of view is about 62cm. The detector arrangement also provides a higher photon fluence at the edge than conventional arrangements centered at the focal point. See fig. 12.

Another advantage is that the dual energy filter is located at or near the source, which provides improved spectral separation. In addition, positioning the dual energy filter at or near the source prevents non-imaging flux from reaching the patient.

Another advantage is that view sampling runs at twice the frame rate. Every other column (or alternating group of columns) two complete data sets are collected in one cycle.

Another advantage is that the dual energy reconstruction method provides maximized time resolution for dual energy acquisition. Furthermore, two complete low-energy and high-energy data sets may also be created using different reference frames. Missing low-energy or high-energy data may be filled in or complemented using conjugation methods, interpolation, machine learning, etc.

As such, the dual energy CT scanner described herein provides improved spatial and temporal resolution over conventional designs by splitting the X-ray spectrum at the source along the detector channel dimension and using selected filter materials (e.g., au and Mo) to improve the acquired energy and contrast resolution. In addition, CT scanners also provide complete sampling of low and high energy data sets required for image reconstruction.

Method of

In some embodiments, the present technology provides methods for obtaining medical images (e.g., CT scans, magnetic Resonance Imaging (MRI) scans, positron Emission Tomography (PET) scans, single Photon Emission Computed Tomography (SPECT) scans, photon counting computed tomography (photon counting computed tomography) scans, or portal images or scans (e.g., scanning projection radiographic images)). Although an exemplary method for obtaining a CT scan is described, the present technology is not limited to methods for obtaining CT scans and includes embodiments for obtaining other types of medical images.

In some embodiments, the CT scan is performed by: (1) positioning a patient in a patient positioning device; (2) Adjusting the portal tilt angle to match the spine angle of the patient; (3) positioning the CT ring around the patient and the positioning device; (4) A source operating at about 140kVp (in other embodiments, the source operates in a range of about 10kVp to about 200 kVp) acquires a scan; (5) An appropriate filter is inserted in the 140kVp X-ray beam path to produce a given spectrum: a first material (e.g., gold) low energy, a second material (e.g., molybdenum) high energy, and alternating first and second material windows (e.g., dual energy); (6) CT Ring scans the desired patient window.

In some embodiments, the method includes providing a patient positioning system to hold the patient in an upright position (e.g., seated and reclined, seated and forward-tilted, standing and reclined, standing and forward-tilted, kneeling and forward-tilted, or kneeling and backward-tilted, or other upright or substantially upright position). See, for example, international patent application publication No. WO 2019/056055 and U.S. patent application publication No. 2020/0268327, each of which is incorporated herein by reference.

In some embodiments, for example, as shown in fig. 28, a method 400 of obtaining and creating CT images is illustrated. The method 400 in the illustrated embodiment is divided into a CT setup phase, a CT scan phase, a data preparation phase, an analytical reconstruction phase, an artifact reduction phase, and an iterative reconstruction phase.

With continued reference to FIGURE 28, the CT setup phase of method 400 includes positioning the patient with respect to the CT scanner (step 404), positioning the CT scanner ring on a z-axis around the patient (step 408), and moving the dual energy filter into the X-ray beam (step 412).

The CT scanning phase of method 400 includes translating the CT ring in the z-direction while rotating the source and the at least one detector about the axis (step 416). In some embodiments, the source and at least one detector translate along an axis while rotating about the axis (helical acquisition). The at least one detector is configured to detect an output from the source (e.g., the detector measures X-ray attenuation). Step 416 further includes recording the output signal from the at least one detector as sampled data. In other words, the detector output signal is sampled at a given time to provide detector samples associated with that time period. In some embodiments, the sampled data is stored on a memory, network, or other suitable data storage scheme.

The data preparation phase of method 400 includes dividing the sampled data into a first data set and a second data set (step 420) (dividing the raw data into a low energy sinogram and a high energy sinogram). The method 400 includes complementing the first dataset with a data complementing module to create a first complete dataset, and complementing the second dataset with a data complementing module to create a second complete dataset (step 424). As described herein, the data complement module in some embodiments utilizes conjugate data to create a complete data set. In other embodiments, the data complement module utilizes high order interpolation. In other embodiments, the data complement module utilizes a machine learning method. In other embodiments, the data complement module utilizes any combination of the data complement schemes described herein. In some embodiments, the first data set and/or the second data set are transformed (rearranged) from a first geometric reference frame (e.g., a native isocenter) to a second geometric reference frame (e.g., fan-beam or parallel) (step 428).

With continued reference to fig. 28, the method 400 includes reconstructing a first CT image using the complete first dataset (step 432) and reconstructing a second CT image using the complete second dataset (step 436) (analysis reconstruction phase). In some embodiments, the method 400 further includes performing correction of image artifacts in the low-energy image and the high-energy image (steps 440 and 444) using any number of suitable artifact reduction techniques (artifact reduction stage).

With continued reference to fig. 28, in some embodiments, the method 400 includes an iterative reconstruction stage that includes iterating through the reconstructed first CT image (step 448). In some embodiments, the method 400 further includes iterating (step 452) on the reconstructed second CT image.

In some embodiments, the method includes obtaining (e.g., acquiring, recording, etc.) a medical image. In some embodiments, it includes obtaining (e.g., acquiring, recording, etc.) a CT image, MRI image, PET image, SPECT image, photon counting computed tomography image, or a portal image or scanning projection radiographic image (e.g., a "scout" scan). In some embodiments, the method includes activating an imaging source (e.g., an electromagnetic radiation source, an X-ray source, a gamma ray source, a radio wave source, a photon source, a proton source, a positron source, a gamma ray source (e.g., gamma rays from a positron source)). In some embodiments, the method includes activating an imaging detector (e.g., an electromagnetic radiation detector, an X-ray detector, a photon detector, a gamma ray detector), e.g., to detect electromagnetic radiation, X-rays, gamma rays, radio waves, photons, protons, positrons, etc., using the detector.

In some embodiments related to CT scanning methods, the method includes generating X-rays using an X-ray generator of a scanner ring. In some embodiments, the method includes detecting X-rays using an X-ray detector of a scanner ring. In some embodiments, the method includes rotating the X-ray generator and the opposing X-ray detector about the patient. In some embodiments, the method includes rotating the X-ray generator and the opposing X-ray detector about the patient while the scanner ring is stationary relative to the gantry arm. In some embodiments, the method includes rotating the X-ray generator and the opposing X-ray detector about the patient while the scanner ring moves relative to the gantry arm.

System and method for controlling a system

The present technology provides embodiments of a system. For example, the present technology provides a multi-axis medical imaging system. In some embodiments, the medical imaging system is a Computed Tomography (CT) system, a Magnetic Resonance Imaging (MRI) system, a Positron Emission Tomography (PET) system, a Single Photon Emission Computed Tomography (SPECT) system, a photon counting computed tomography system, or a portal imaging system or a scanning projection radiography imaging system. Although the present technology is described with respect to an exemplary embodiment in which the medical imaging system is a Computed Tomography (CT) system, the present technology is not limited to CT scanning systems and embodiments should be understood to include other types of medical imaging systems.

In some embodiments, the system includes a multi-axis medical imaging device as described herein, as well as software components and/or hardware components configured to rotate the gantry and/or translate the scanner ring. In some embodiments, the system includes software components configured to perform the methods as described herein. In some embodiments, the system includes a multi-axis medical imaging device, software for obtaining (e.g., recording, acquiring) medical images, and software for controlling gantry rotation and scanner ring translation.

In some embodiments, a system includes a multi-axis medical imaging device and a controller as described herein. In some embodiments, a medical imaging source and detector are in communication with the controller. In some embodiments, the controller activates the medical imaging source and collects image projections from the detector. In some embodiments, the controller controls the relative movement of the medical imaging source and the detector about the scanner ring. In some embodiments, the controller communicates with a camera (e.g., a horizontal camera and/or a vertical camera) positioned to obtain a facade image and/or a planar image of the area occupied by the patient. In some embodiments, the controller communicates with a graphical display terminal for providing output images, such as tomographic images, positioning information, and a user input device, such as a keyboard, for receiving instructions from a user. In some embodiments, the controller has a general-purpose computer architecture that includes one or more processors in communication with a memory for storing a non-transitory control program (e.g., for storing a tomographic projection set and resulting tomographic images).

In some embodiments, the system includes a multi-axis medical imaging device that includes one or more cameras (e.g., a scanner ring that includes one or more cameras). In some embodiments, the camera records an image that is subsequently processed by software (e.g., a microprocessor, a graphics processor, a communication bus, configured to communicate, record, analyze, store, manipulate, and/or compare images) and/or hardware components (e.g., a microprocessor, a graphics processor, a communication bus, configured to perform image recording, image analysis, image storage, image processing, and/or image comparison methods) of the imaging subsystem.

In some embodiments, the system includes a multi-axis CT scanner as described herein, as well as software components and/or hardware components configured to rotate the gantry and/or translate the scanner ring. In some embodiments, the system includes software components configured to perform the methods as described herein.

In some embodiments, the system includes a multi-axis CT scanner, software for obtaining (e.g., recording, acquiring) CT scans, and software for controlling gantry rotation and scanner ring translation.

In some embodiments, a system includes a multi-axis CT scanner as described herein, a patient in an upright (e.g., a vertical (e.g., substantially and/or substantially vertical position)), and a user interacting with controls configured to move the multi-axis CT scanner and acquire a CT scan of the patient or a portion thereof.

Some portions of this specification describe embodiments of the present technology in terms of algorithms and symbolic representations of operations on information. These algorithmic descriptions and representations are the means used by those skilled in the data processing arts to effectively convey the substance of their work to others skilled in the art. These operations, while described functionally, computationally, or logically, are understood to be implemented by computer programs or equivalent circuits, microcode, or the like. Furthermore, it has sometimes proven convenient at times, to refer to these arrangements of operations as modules, without loss of generality. The described operations and their associated modules may be implemented in software, firmware, hardware, or any combination thereof.

Some of the steps, operations, or processes described herein may be performed or implemented using one or more hardware or software modules, alone or in combination with other devices. In some embodiments, the software modules are implemented with a computer program product comprising a computer readable medium containing computer program code executable by a computer processor for performing any or all of the steps, operations, or processes described.

In some embodiments, the system includes a computer and/or data store that is provided virtually (e.g., as a cloud computing resource). In particular embodiments, the present technology includes using cloud computing to provide a virtual computer system that includes components of and/or performs the functions of a computer as described herein. Thus, in some embodiments, cloud computing provides infrastructure, applications, and software as described herein over a network and/or over the internet. In some embodiments, computing resources (e.g., data analysis, computing, data storage, applications, file storage, etc.) are provided remotely over a network (e.g., the internet).

Embodiments of the present technology may also relate to an apparatus for performing the operations herein. The apparatus may be specially constructed for the required purposes, and/or it may comprise a general-purpose computing device selectively activated or reconfigured by a computer program stored in the computer. Such a computer program may be stored in a non-transitory tangible computer readable storage medium or any type of medium suitable for storing electronic instructions, which may be coupled to a computer system bus. Furthermore, any of the computing systems mentioned in this specification may include a single processor or may be an architecture employing a multi-processor design to increase computing power.

In some embodiments, the present technology (e.g., system) includes an image reconstruction component (e.g., a hardware component and/or a software component) within the scanner loop, and the image reconstruction component is configured to generate (e.g., reconstruct) a medical image, for example, from raw data (e.g., from raw image data). In some embodiments, the present technology (e.g., system) includes a data transmission component that communicates raw image data acquired by a scanner loop (e.g., acquired by a detector of the scanner loop) to a component configured to generate (e.g., reconstruct) a medical image. In some embodiments, the scanner ring includes a data transmission component and the component configured to generate (e.g., reconstruct) the medical image is separate from the medical imaging device (e.g., connected to a computer of the medical imaging device through a wired and/or wireless communication component).

Use of the same

In some embodiments, the techniques provided herein may be used in medical, clinical, and research environments. For example, in some embodiments, the present techniques may be used to image biological systems, such as organisms (e.g., animals, humans), organs, tissues, and/or cells. In some embodiments, the present techniques may be used to image the head, neck, lungs, heart, circulatory system (e.g., arteries and/or veins), abdomen, pelvic region, gastrointestinal system, axial skeleton (e.g., spine), kidneys, and/or limbs. For example, in some embodiments, the present techniques may be used to diagnose and/or treat diseases and/or injuries. For example, the present technology may be used in preventive medicine, disease screening, disease diagnosis, disease treatment, and/or disease monitoring. For example, in some embodiments, the present technology may be used to diagnose and/or treat cancer. In some embodiments, the present techniques may be used to image the chest, for example, for diagnosis of pneumothorax, emphysema, cardiac hypertrophy, fibrosis, diaphragmatic hernia, empyema, atelectasis, pneumonia, pulmonary edema, pulmonary hemorrhage, primary pulmonary malignancy, or metastatic disease. In some embodiments, the present techniques may be used to diagnose and/or treat calcification, bone trauma, hemorrhage, edema, infarction, and/or tumors. The present technology may also be used in research environments, such as imaging animals, humans, organs or tissues for research purposes. The present technology may also be used in veterinary medical environments, such as imaging animals, organs or tissues for diagnosis and/or treatment. In some embodiments, the present technology may be used for industrial purposes, such as imaging non-biological objects, such as for identifying structural features, material defects, internal content, etc., without breaking or otherwise damaging the non-biological objects.

While the disclosure herein relates to certain illustrated embodiments, it is to be understood that these embodiments are presented by way of example, and not by way of limitation. All publications and patents mentioned in the above specification are herein incorporated by reference in their entirety for all purposes. Various modifications and variations of the described compositions, methods, and uses of the technology will be apparent to those skilled in the art without departing from the scope and spirit of the technology described. Although the present technology has been described in connection with specific exemplary embodiments, it should be understood that the invention as claimed should not be unduly limited to such specific embodiments. Indeed, various modifications of the described modes for carrying out the invention which are obvious to those skilled in the art are intended to be within the scope of the following claims.

Claims (26)

1. A Computed Tomography (CT) scanner, comprising:

A source positioned a first distance from a center, wherein the source is rotatable about the center; and

A plurality of detectors rotatable about the center, wherein the plurality of detectors are positioned at a plurality of distances from the source.

2. The scanner of claim 1, wherein each of the plurality of detectors is positioned a second distance from the center.

3. The scanner of claim 2, wherein the first distance is greater than the second distance.

4. The scanner of claim 1, wherein each of the plurality of detectors is directed toward the source.

5. The scanner of claim 4, wherein each of the plurality of detectors includes a detector face defining an input plane, and wherein the input plane is orthogonal to an incident beam from the source.

6. The scanner of claim 1, wherein each of the plurality of detectors is oriented toward the center.

7. The scanner of claim 1, wherein each of the plurality of detectors is oriented such that an edge is aligned with an edge of an adjacent detector.

8. The scanner of claim 1, wherein the plurality of detectors define a field of view of at least 50 centimeters.

9. The scanner of claim 1, wherein the CT scanner is movable between an upright configuration, a tilted configuration, and a horizontal configuration.

10. A Computed Tomography (CT) scanner, comprising:

A source defining an imaging plane; and

A filter comprising a first filter portion comprising a first material, a second filter portion comprising a second material, and a third filter portion comprising the first material and the second material;

wherein the filter is movable relative to the source to align any of the first, second and third filter portions with the imaging plane.

11. The scanner of claim 10, wherein the third filter portion comprises alternating columns of the first material and the second material, wherein each column intersects the imaging plane.

12. The scanner of claim 10, wherein the first material attenuates X-ray spectra by a first amount; and wherein the second material attenuates the X-ray spectrum by a second amount different from the first amount.

13. The scanner of claim 10, wherein the first material has a first mass attenuation coefficient in a range of 0.1cm ²/g to 200cm ²/g corresponding to an excitation in a range of 10 to 200kVp and the second material has a second mass attenuation coefficient corresponding to the excitation that is different from the first mass attenuation coefficient.

14. The scanner of claim 10, wherein the first material is gold, and wherein the second material is molybdenum.

15. The scanner of claim 10, wherein the first material is gold, and wherein the second material is tin.

16. The scanner of claim 10, wherein the third filter portion is located between the first filter portion and the second filter portion.

17. The scanner of claim 10, wherein the filter defines a radius.

18. The scanner of claim 10, further comprising a filter adjustment assembly having a motor, a frame, and a linkage coupled between the motor and the frame, wherein the filter is coupled to the frame.

19. The scanner of claim 10, wherein the first filter portion at least partially overlaps the third filter portion and the second filter portion at least partially overlaps the third filter portion.

20. A method of creating a CT image, comprising:

rotating the source and the at least one detector about an axis; wherein the at least one detector is configured to detect an output from the source;

Recording an output signal from the at least one detector as sampled data;

Dividing the sampled data into a first data set and a second data set;

complementing the first dataset with a data complementing module to create a first complete dataset;

Complementing the second dataset with the data complementing module to create a second complete dataset;

Reconstructing a first CT image using the first complete data set; and

A second CT image is reconstructed using the second complete data set.

21. The method of claim 20, wherein the data complement module utilizes conjugated data.

22. The method of claim 20, wherein the data complement module utilizes high order interpolation.

23. The method of claim 20, wherein the data complement module utilizes a machine learning method.

24. The method of claim 20, further comprising iterating through reconstructing the first CT image and/or the second CT image.

25. The method of claim 20, wherein the source and the at least one detector translate along the axis while rotating about the axis.

26. The method of claim 20, further comprising transforming the first dataset from a first geometric reference frame to a second geometric reference frame.