CN114299046A - Medical image registration method, device, equipment and storage medium - Google Patents
Medical image registration method, device, equipment and storage medium Download PDFInfo
- Publication number
- CN114299046A CN114299046A CN202111664944.5A CN202111664944A CN114299046A CN 114299046 A CN114299046 A CN 114299046A CN 202111664944 A CN202111664944 A CN 202111664944A CN 114299046 A CN114299046 A CN 114299046A
- Authority
- CN
- China
- Prior art keywords
- medical image
- medical
- information
- registration
- registered
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Abstract
The embodiment of the specification discloses a medical image registration method, a device, equipment and a storage medium, and the scheme comprises the following steps: acquiring a first medical image set to be registered, wherein the first medical image set to be registered is a set of medical images shot by a first user in a medical visit process; dividing a first to-be-registered medical image set into a first medical image subset based on the medical image characteristic information; acquiring a second medical image set used as a registration reference, wherein the second medical image set used as the registration reference is a set of medical images shot by the first user in another medical visit process; dividing the second medical image set used as a registration reference into a second medical image subset based on the medical image characteristic information; and taking any medical image subset in the second medical image set as a registration reference, and registering the medical image subset corresponding to any medical image subset in the first medical image set to be registered to obtain a registration result.
Description
Technical Field
The present application relates to the field of medical image processing technologies, and in particular, to a medical image registration method, apparatus, device, and storage medium.
Background
When medical image analysis is performed, several related images of the same patient are often put together for comprehensive analysis, that is, the medical images are registered, so that comprehensive information of the patient in various aspects is obtained, and the level of medical diagnosis and treatment is improved. When a user performs a physical examination, a plurality of examinations are sometimes performed, for example, a head and a chest are both examined in one physical examination, and medical images taken in one examination are generally stored in one folder. Therefore, the doctor needs to manually select the medical images needing to be registered from the file folder in the film reading process, the time cost is high, and the doctor cannot quickly read the films conveniently.
Therefore, there is a need for a method for medical image reading by doctors.
Disclosure of Invention
The embodiment of the specification provides a medical image registration method, a medical image registration device, medical image registration equipment and a storage medium, so that a method for enabling a doctor to read medical images conveniently and quickly is provided.
In order to solve the above technical problem, the embodiments of the present specification are implemented as follows:
the embodiment of the present specification provides a medical image registration method, including:
acquiring a first medical image set to be registered, wherein the first medical image set to be registered is a set of medical images shot by a first user in a medical visit process;
dividing the first to-be-registered medical image set into a first medical image subset based on medical image feature information;
acquiring a second medical image set used as a registration reference, wherein the second medical image set used as the registration reference is a set of medical images shot by the first user in another medical visit process;
dividing the second medical image set used as a registration reference into a second medical image subset based on the medical image feature information;
and taking any medical image subset in the second medical image set as a registration reference, and registering the medical image subset corresponding to any medical image subset in the first medical image set to be registered to obtain a registration result.
An embodiment of the present specification provides a medical image registration apparatus, including:
the medical image acquisition module to be registered is used for acquiring a first medical image set to be registered, wherein the first medical image set to be registered is a set of medical images shot by a first user in a medical visit process;
the medical image to be registered dividing module is used for dividing the first medical image set to be registered into a first medical image subset based on the medical image characteristic information;
a reference medical image acquisition module for acquiring a second medical image set used as a reference for registration, wherein the second medical image set used as the reference for registration is a set of medical images shot by the first user in another medical visit;
a reference medical image dividing module for dividing the second medical image set used as a reference for registration into a second medical image subset based on the medical image feature information;
and the medical image registration module is used for registering the medical image subset corresponding to any medical image subset in the first medical image set to be registered by taking any medical image subset in the second medical image set as a registration reference to obtain a registration result.
An embodiment of the present specification provides a medical image registration apparatus, including:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to:
acquiring a first medical image set to be registered, wherein the first medical image set to be registered is a set of medical images shot by a first user in a medical visit process;
dividing the first to-be-registered medical image set into a first medical image subset based on medical image feature information;
acquiring a second medical image set used as a registration reference, wherein the second medical image set used as the registration reference is a set of medical images shot by the first user in another medical visit process;
dividing the second medical image set used as a registration reference into a second medical image subset based on the medical image feature information;
and taking any medical image subset in the second medical image set as a registration reference, and registering the medical image subset corresponding to any medical image subset in the first medical image set to be registered to obtain a registration result.
Embodiments of the present specification provide a computer-readable medium having computer-readable instructions stored thereon, which are executable by a processor to implement a medical image registration method.
One embodiment of the present description achieves the following advantageous effects:
according to the technical scheme, the medical images obtained in the process of medical visit by the user twice are divided according to the characteristic information of the medical images to obtain a plurality of types of medical images corresponding to each other, so that the process of manually classifying the medical images before use is omitted, the time is saved, and the efficiency is improved. Moreover, the same kind of medical images are registered in the medical visiting process twice before and after, and the registration result can be directly called in the subsequent stage when the medical images are used, so that a user can conveniently and quickly obtain the registration result of the medical images.
Drawings
In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without any creative effort.
Fig. 1 is a schematic view of an application scenario of a medical image registration method provided in an embodiment of the present specification;
fig. 2 is a flowchart of a medical image registration method provided in an embodiment of the present specification;
fig. 3 is a schematic diagram illustrating classification results of medical images taken during a certain visit of a subject in a medical image registration method provided by an embodiment of the present specification;
fig. 4 is a schematic structural diagram of an apparatus corresponding to the medical image registration apparatus of fig. 2 provided in an embodiment of the present specification;
fig. 5 is a schematic structural diagram of a medical image registration apparatus corresponding to fig. 2 provided in an embodiment of the present specification.
Detailed Description
To make the objects, technical solutions and advantages of one or more embodiments of the present disclosure more apparent, the technical solutions of one or more embodiments of the present disclosure will be described in detail and completely with reference to the specific embodiments of the present disclosure and the accompanying drawings. It is to be understood that the embodiments described are only a few embodiments of the present specification, and not all embodiments. All other embodiments that can be derived by a person skilled in the art from the embodiments given herein without making any creative effort fall within the scope of protection of one or more embodiments of the present specification.
The meaning of the medical image registration in the present invention is explained first, and when performing medical image analysis, several images of the same patient are often put together for analysis, so as to obtain comprehensive information of the patient in many aspects and improve the level of medical diagnosis and treatment. To perform quantitative analysis on different images, the different images are first strictly aligned, i.e. image registration is achieved. Medical image registration refers to spatially transforming one medical image into spatial correspondence with a corresponding point on another medical image. This coincidence means that the same anatomical point on the body has the same spatial position on the two matching images. The result of the registration should be such that all anatomical points, or at least all points of diagnostic significance and points of surgical interest, on both images match. When medical image analysis is performed, several related images of the same patient are often put together for comprehensive analysis, that is, the medical images are registered, so that comprehensive information of the patient in various aspects is obtained, and the level of medical diagnosis and treatment is improved.
As shown in fig. 1, when a user performs a physical examination, a plurality of examinations are sometimes performed, for example, a head and a chest are examined in one physical examination, and medical images taken in one physical examination are generally stored in one folder. Therefore, the doctor needs to manually select the medical images needing to be registered from the file folder in the film reading process, the time cost is high, and the doctor cannot quickly read the films conveniently.
In order to solve the defects in the prior art, the scheme provides the following embodiments.
In order to explain the technical solution of the present invention in detail, the present solution provides the following embodiments, and it should be firstly explained that relational terms such as "first" and "second" and the like are only used to distinguish one entity or operation from another entity or operation in the present document, and do not necessarily require or imply any actual relation or precedence between the entities or operations.
Fig. 2 is a schematic flowchart of an overall scheme of a medical image registration method in an embodiment of the present disclosure. As shown in fig. 2, from the viewpoint of a program, the execution subject of the flow may be a program installed in an application server or an application client.
As shown in fig. 2, the process may include the following steps:
step S202: a first set of medical images to be registered is acquired, which is a set of medical images taken by a first user during a medical visit.
The medical image to be registered may represent a medical image taken by the first user with the relevant medical device while performing a physical examination. The first user may refer to a user who needs to perform a related medical image photographing, such as a subject of a clinical trial project, a patient with a disease, or a staff performing a health examination, etc. The medical images to be registered, which are obtained during the physical examination of the first user, are stored in a folder.
It should be noted that, when the first user performs a physical examination, different parts may need to be examined according to the physical health condition of the first user and according to the requirement of the first user or following the doctor instruction, for example, a certain first user needs to examine the head, the chest, the abdominal cavity, the four limbs or a certain organ of the first user, and a plurality of medical images may be taken of the same part, for example, when the first user performs a head CT examination, a plurality of head CT medical images may be taken.
Different types of medical equipment may be used during the examination to obtain medical images of different modalities, for example, a first user may use a medical imaging device such as CT, Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), etc. during the physical examination.
In the technical scheme of the embodiment, a process that a first user needs to shoot a first number of medical images to be registered in the process of physical examination is called a medical visit.
Step S204: the first set of medical images to be registered is divided into a first subset of medical images based on medical image feature information.
The medical image feature information may refer to information used to distinguish or merge different medical images, and for a medical image, the medical image feature information may specifically be information of a modality, a position, a layer thickness, a part, and the like. The first set of medical images to be registered in step S202 may be divided into a first subset of medical images according to the medical image feature information, that is, in the medical images to be registered, the medical images having the same medical image feature information are divided into the same subset of medical images.
It should be noted that the medical image feature information may be divided into different levels, for example, in terms of medical image feature information of a level of "part", when the first user inspects a body "part" of the head, in order to acquire multi-aspect information of the head of the first user, a medical image of head CT may be obtained by detecting the "part" of the head of the first user by using a CT medical imaging apparatus, and a PET image of the head may be obtained by detecting the "part" of the head of the first user by using a PET apparatus, so in this example, if the combined information of "modality" and "part" is used as the medical image feature information, since the medical images detected by using the CT medical imaging apparatus and the PET apparatus have different modalities, even though both are the medical image of the part of the "head", but should also be divided into different subsets of medical images due to having different modalities.
The technical scheme of the embodiment does not limit the specific use standard of the medical image characteristic information, does not limit the hierarchy of the medical image characteristic information, and can carry out corresponding setting according to specific requirements.
Step S206: acquiring a second medical image set used as a registration reference, wherein the second medical image set used as the registration reference is a set of medical images shot by the first user in another medical visit.
In the technical solution of the present embodiment, the second medical image set used as the reference for registration may refer to a set of medical images taken by the first user during another medical visit, according to the requirement of medical detection, the medical images of different time periods of the user may need to be compared, this thus requires registration of medical images of different time periods, such as a medical visit by the user at the beginning of 3 months of the year, after another medical visit is made at the end of 3 months in the same year, in this context, a medical image taken by a certain medical visit can be selected as a reference for registration, specifically, in this example, for example, a medical image captured at the beginning of 3 months during medical visit may be selected as a reference for medical image registration, and for example, information about whether the lesion of the first user is enlarged or not may be obtained by performing comparative analysis after the medical image of the lesion of the first user at the end of 3 months is registered with the medical image of the lesion of the first user at the beginning of 3 months.
Step S208: dividing the second medical image set used as a registration reference into a second medical image subset based on the medical image feature information.
In the present embodiment, the second medical image set used as the reference for registration is divided into second medical image subsets according to the same medical image feature information as in step S204, and each medical image subset includes a number of medical images having the same medical image feature information.
It should be noted that, in step S206, during another medical visit, the number of medical images used as a reference for registration obtained by the user may be different from the number of medical images to be registered in step S202, and during two previous visits and two subsequent visits, the medical images used as a reference for registration and the medical images to be registered are classified based on the medical image feature information of the same level, and the number of medical images in the same category of medical image subset obtained may also be different, and in a specific embodiment, the difference number may be limited within a predetermined number range, or within a predetermined proportion range, for example, the difference may not exceed 20, or the difference may not be greater than 20%, or the difference of medical image data is within 5% -20%.
Step S210: and taking any medical image subset in the second medical image set as a registration reference, and registering the medical image subset corresponding to any medical image subset in the first medical image set to be registered to obtain a registration result.
In the technical scheme of the embodiment, after medical images obtained at different visiting stages are classified, the medical images in the medical image subset capable of performing medical image registration can be registered as much as possible, so that the registration result can be called directly at the subsequent stage conveniently.
It should be noted that, in an actual solution, the number of sets in the first medical image subset may be different from the number of sets in the second medical image subset, for example, in an alternative embodiment, in step S202, in order to examine the body of the first user as fully as possible, a few more medical images are captured, and in step S206, when the first user performs another medical visit, because there is a radiation hazard when performing medical image capturing, on the premise that the general condition of the body of the first user is known, the number of medical images captured at this visit may be less than that of the first time, so as to reduce the harm of radiation to the body of the first user as much as possible on the premise that the requirement is met.
In the technical solution of this embodiment, an existing registration method may be adopted to perform registration of a medical image, such as a registration method trained through a neural network, a supervised learning-based registration method, or an unsupervised learning-based registration method, and for a specific registration method, the technical solution of this embodiment is not limited.
According to the technical scheme, the medical images obtained in the process of medical visit by the user twice are divided according to the characteristic information of the medical images to obtain a plurality of types of medical images corresponding to each other, so that the process of manually classifying the medical images before use is omitted, the time is saved, and the efficiency is improved. Moreover, the same kind of medical images are registered in the medical visiting process twice before and after, and the registration result can be directly called in the subsequent stage when the medical images are used, so that a user can conveniently and quickly obtain the registration result of the medical images.
Based on the method of fig. 2, the present specification also provides some specific embodiments of the method, which are described below.
In an optional embodiment, an image format of a medical image in the first medical image set to be registered and/or the second medical image set is a DICOM file format.
Dicom (digital imaging and communication in medicine), an international standard for medical images and related information (ISO 12052). DICOM is widely used in radiomedicine, cardiovascular imaging and radiodiagnosis and treatment equipment (X-ray, CT, nuclear magnetic resonance, ultrasound, etc.), and at present, for example, CT, nuclear magnetic resonance, ultrasound, etc. utilize precisely collimated X-ray beam, gamma ray, ultrasound, etc. to perform cross-sectional scanning one by one around a certain part of a human body together with a detector with extremely high sensitivity, so that the images obtained after scanning are multi-layer images, and the images of each layer can be stacked on a z-axis to form a three-dimensional image.
In an optional embodiment, the medical image feature information is determined by label information of the medical image. The label information of the medical image, which may also be referred to as tag information of the medical image, is used to describe attribute information of the medical image. The medical images may be classified at different levels based on specific attribute information in the label information of the medical images, as set forth below.
For example, in an optional embodiment, since the medical image tag information includes modality information, the determining of the medical image feature information from the medical image tag information includes:
the medical image feature information is configured by modality information included in tag information of the medical image as first reference information.
In a further optimization scheme, in an optional embodiment, the tag information further includes body part information to which the medical image belongs, and the determining of the medical image feature information by the tag information of the medical image includes:
and combining the first reference information and the second reference information by taking the body part information to which the medical image belongs as second reference information to construct first medical image characteristic information.
In an optional embodiment, the tag information further includes state information of the medical image, and the determining of the medical image feature information from the tag information of the medical image includes:
and combining the first reference information, the second reference information and the third reference information by taking the state information of the medical image as third reference information to construct second medical image characteristic information.
In an optional embodiment, the tag information further includes layer thickness information corresponding to the medical image, and the determining of the medical image feature information from the tag information of the medical image includes:
and combining the first reference information, the second reference information, the third reference information and the fourth reference information by taking the layer thickness information corresponding to the medical image as fourth reference information to construct third medical image feature information.
In an optional embodiment, the tag information further includes serial image number information, and the determining of the medical image feature information from the tag information of the medical image includes:
and combining the first reference information, the second reference information, the third reference information, the fourth reference information and the fifth reference information by taking the number information of the sequence images as fifth reference information to construct fourth medical image feature information.
In the foregoing technical solution, based on attribute information of different dimensions of a medical image, medical image feature information of different levels can be constructed, and then different fine-grained classifications are performed on a first to-be-registered medical image set and a second medical image set according to the medical image feature information of different levels, so as to meet analysis requirements of a user on different levels of the medical image. Moreover, in an optional embodiment, when registering the medical images, cross-modality registration may be performed, specifically, for example, information of body parts to which the two medical images belong and thickness information of the state information layer are the same, and if the difference is that the modalities are different, cross-modality registration may be performed on the two medical images belonging to different modalities, in other words, cross-comparison may be performed to analyze the medical images from multiple angles.
In an optional embodiment, in the technical solution, the registering, with any one medical image subset in the second medical image set as a registration reference, a medical image subset corresponding to the any one medical image subset in the first medical image set to be registered specifically includes:
acquiring a history habit record of a second user for performing cross-modal registration on the medical image;
registering, based on the historical habit record, medical image sequences of different modalities belonging to the same part in the first and second medical image subsets.
The second user may refer to a user who performs analysis utilization on the medical image, such as a doctor in a hospital, who may use the medical image across modalities, such as a CT image and a PET image of the head, according to the usage habit of the medical image by an individual, thereby performing comprehensive analysis on the head pathology. In the technical scheme of the embodiment, the history habit of the cross-modal registration of the medical image by the doctor is recorded, and the registration result is obtained in advance according to the history habit, so that the doctor can conveniently obtain the registration result of the medical image corresponding to the habit of the doctor in the subsequent stage when using the medical image, and the user friendliness of the scheme of the invention is enhanced.
In an optional embodiment, in the subset of medical images, the difference between the number of medical images in the corresponding subset of medical images and the number of medical images in the subset of medical images is less than or equal to 5% -20% of the number of images in the subset of medical images.
In an optional embodiment technical solution, the registering, with any medical image subset in the second medical image set as a registration reference, a medical image subset corresponding to the any medical image subset in the first medical image set to be registered, and after obtaining a registration result, further includes:
and storing the registration result in a cloud server.
In an optional embodiment, after storing the registration result in the cloud server, the method includes:
receiving a request to be registered sent by a client, wherein the request to be registered comprises a first medical image to be registered selected by a target user; determining one or more second medical images to be registered based on the first medical image to be registered, and returning the one or more second medical images to be registered to the client as recommendation information; receiving a registration request sent by the client, wherein the registration request comprises a target medical image to be registered in the one or more second medical images to be registered; in response to the registration request, retrieving and returning a registration result of the first medical image to be registered and the target medical image to be registered from the registration result.
Taking fig. 3 as an example to illustrate the technical solution of this alternative embodiment, fig. 3 is a schematic diagram of a classification result of a medical image taken by a subject during a certain visit in a medical image registration method provided in an embodiment of this specification, and fig. 3 classifies the medical image taken by the subject during the visit by using the third medical image feature information set forth above, and since the third medical image feature information includes the reference information of the number of sequential images, as shown in fig. 3, under a frame of "CT, horizontal position, 5mm layer thickness, and chest" (according to the division standard of the medical image feature information set forth above, the line where the frame is located is equivalent to the division standard of the third medical image feature information), the line of the sub-frame is obtained by taking the third medical image characteristic information as a division standard), and A and B represent different sequence numbers. Correspondingly, under the frame "CT, cross-section, 1mm layer thickness, breast", two sub-frames such as C and D can be subdivided, C and D representing different numbers of sequences.
Taking the subframe of a as an example, the registration result recommendation scheme of the embodiment is explained below, when the subframe a is registered with the medical image obtained by a certain visit as the registration reference, and the medical image obtained by the certain visit as the registration reference is divided according to the dividing method in fig. 3, subframes such as a ', B', C ', D' can also be obtained, for example, subframes obtained by further dividing a 'and B' by the criterion of "CT, transverse position, 5mm layer thickness, chest" according to the number of sequence images. The scheme not only recommends the registration results of A and A 'to the user, but also recommends the registration results of A and B' to the user.
In the technical scheme of the embodiment, the registration result is stored in the cloud server, and specifically, the registration result can be stored in a Redis database.
Based on the same idea, the embodiment of the present specification further provides a device corresponding to the above method. Fig. 4 is a schematic structural diagram of a medical image registration apparatus corresponding to fig. 2 provided in an embodiment of the present specification. As shown in fig. 4, the apparatus may include:
a to-be-registered medical image acquisition module 402, configured to acquire a first to-be-registered medical image set, where the first to-be-registered medical image set is a set of medical images captured by a first user in a medical visit process;
a to-be-registered medical image dividing module 404, configured to divide the first to-be-registered medical image set into a first medical image subset based on medical image feature information;
a reference medical image acquisition module 406, configured to acquire a second medical image set serving as a reference for registration, where the second medical image set serving as the reference for registration is a set of medical images taken by the first user during another medical visit;
a reference medical image dividing module 408 for dividing the second medical image set used as a reference for registration into a second medical image subset based on the medical image feature information;
a medical image registration module 410, configured to use any medical image subset in the second medical image set as a registration reference, and register a medical image subset corresponding to any medical image subset in the first medical image set to be registered, so as to obtain a registration result.
Based on the same idea, the embodiment of the present specification further provides a device corresponding to the above method.
Fig. 5 is a schematic structural diagram of a medical image registration apparatus corresponding to fig. 2 provided in an embodiment of the present specification. As shown in fig. 5, the apparatus 500 may include:
at least one processor 510; and the number of the first and second groups,
a memory 530 communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory 530 stores instructions 520 executable by the at least one processor 510 to enable the at least one processor 510 to:
acquiring a first medical image set to be registered, wherein the first medical image set to be registered is a set of medical images shot by a first user in a medical visit process;
dividing the first to-be-registered medical image set into a first medical image subset based on medical image feature information;
acquiring a second medical image set used as a registration reference, wherein the second medical image set used as the registration reference is a set of medical images shot by the first user in another medical visit process;
dividing the second medical image set used as a registration reference into a second medical image subset based on the medical image feature information;
and taking any medical image subset in the second medical image set as a registration reference, and registering the medical image subset corresponding to any medical image subset in the first medical image set to be registered to obtain a registration result.
Based on the same idea, the embodiment of the present specification further provides a computer-readable medium corresponding to the above method. The computer readable medium has computer readable instructions stored thereon that are executable by a processor to implement the method of:
acquiring a first medical image set to be registered, wherein the first medical image set to be registered is a set of medical images shot by a first user in a medical visit process;
dividing the first to-be-registered medical image set into a first medical image subset based on medical image feature information;
acquiring a second medical image set used as a registration reference, wherein the second medical image set used as the registration reference is a set of medical images shot by the first user in another medical visit process;
dividing the second medical image set used as a registration reference into a second medical image subset based on the medical image feature information;
and taking any medical image subset in the second medical image set as a registration reference, and registering the medical image subset corresponding to any medical image subset in the first medical image set to be registered to obtain a registration result.
All the embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments may be referred to each other, and the related parts may be referred to the parts of the description of the method embodiments.
In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose logic functions are determined by programming the device by a user. A digital character system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate a dedicated integrated circuit chip. Furthermore, nowadays, instead of manually making integrated circuit chips, such programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is written by a specific programming language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as abel (advanced library expression language), ahdl (altera hardwaredescription language), traffic, pl (core universal programming language), HDCal, jhddl (hardwaredescription language), languava, Lola, HDL, pamm, hardsrapld script (hardware descriptor) and vhigh-language (hardware description language, which is currently used by the most popular languages. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.
The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: ARC625D, atmel at91SAM, microchip pic18F26K20, and silicon labsc8051F320, the memory controller may also be implemented as part of the control logic of the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be considered a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functionality of the units may be implemented in one or more software and/or hardware when implementing the present application.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Disks (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission medium which can be used to store information which can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The application may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The application may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (14)
1. A medical image registration method, comprising:
acquiring a first medical image set to be registered, wherein the first medical image set to be registered is a set of medical images shot by a first user in a medical visit process;
dividing the first to-be-registered medical image set into a first medical image subset based on medical image feature information;
acquiring a second medical image set used as a registration reference, wherein the second medical image set used as the registration reference is a set of medical images shot by the first user in another medical visit process;
dividing the second medical image set used as a registration reference into a second medical image subset based on the medical image feature information;
and taking any medical image subset in the second medical image set as a registration reference, and registering the medical image subset corresponding to any medical image subset in the first medical image set to be registered to obtain a registration result.
2. The medical image registration method of claim 1, wherein the medical image feature information is determined from tag information of a medical image.
3. The medical image registration method of claim 2, wherein the tag information includes modality information, the medical image feature information being determined from tag information of a medical image comprises:
the medical image feature information is configured by modality information included in tag information of the medical image as first reference information.
4. The method of claim 3, wherein the tag information further includes body-part information to which the medical image belongs, and the medical-image feature information is determined by the tag information of the medical image includes:
and combining the first reference information and the second reference information by taking the body part information to which the medical image belongs as second reference information to construct first medical image characteristic information.
5. The method of claim 4, wherein the tag information further includes state information of the medical image, the medical image feature information being determined from the tag information of the medical image comprises:
and combining the first reference information, the second reference information and the third reference information by taking the state information of the medical image as third reference information to construct second medical image characteristic information.
6. The method of claim 5, wherein the label information further includes layer thickness information corresponding to the medical image, the medical image characteristic information being determined from the label information of the medical image comprises:
and combining the first reference information, the second reference information, the third reference information and the fourth reference information by taking the layer thickness information corresponding to the medical image as fourth reference information to construct third medical image feature information.
7. The method of claim 6, wherein the label information further includes sequential image quantity information, the medical image feature information determined from the label information of the medical image includes:
and combining the first reference information, the second reference information, the third reference information, the fourth reference information and the fifth reference information by taking the number information of the sequence images as fifth reference information to construct fourth medical image feature information.
8. The medical image registration method according to claim 1, wherein the registering, with any one of the subsets of medical images in the second medical image set as a registration reference, a subset of medical images in the first medical image set to be registered corresponding to the any one of the subsets of medical images to obtain a registration result includes:
acquiring a history habit record of a second user for performing cross-modal registration on the medical image;
registering, based on the historical habit record, medical image sequences of different modalities belonging to the same part in the first and second medical image subsets.
9. The medical image registration method of claim 1, wherein the difference between the number of medical images in any one of the subsets of medical images and the number of medical images in the corresponding subset of medical images is less than or equal to 5% -20% of the number of images in any one of the subsets of medical images.
10. The medical image registration method according to claim 1, wherein the registering, with any subset of the medical images in the second medical image set as a registration reference, a subset of the medical images in the first medical image set to be registered corresponding to the any subset of the medical images, and after obtaining a registration result, further comprises:
and storing the registration result in a cloud server.
11. The medical image registration method of claim 10, wherein the saving the registration result in a cloud server comprises:
receiving a request to be registered sent by a client, wherein the request to be registered comprises a first medical image to be registered selected by a target user; determining one or more second medical images to be registered based on the first medical image to be registered, and returning the one or more second medical images to be registered to the client as recommendation information; receiving a registration request sent by the client, wherein the registration request comprises a target medical image to be registered in the one or more second medical images to be registered; in response to the registration request, retrieving and returning a registration result of the first medical image to be registered and the target medical image to be registered from the registration result.
12. A medical image registration apparatus, characterized by comprising:
the medical image acquisition module to be registered is used for acquiring a first medical image set to be registered, wherein the first medical image set to be registered is a set of medical images shot by a first user in a medical visit process;
the medical image to be registered dividing module is used for dividing the first medical image set to be registered into a first medical image subset based on the medical image characteristic information;
a reference medical image acquisition module for acquiring a second medical image set used as a reference for registration, wherein the second medical image set used as the reference for registration is a set of medical images shot by the first user in another medical visit;
a reference medical image dividing module for dividing the second medical image set used as a reference for registration into a second medical image subset based on the medical image feature information;
and the medical image registration module is used for registering the medical image subset corresponding to any medical image subset in the first medical image set to be registered by taking any medical image subset in the second medical image set as a registration reference to obtain a registration result.
13. A medical image registration apparatus, characterized by comprising:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to:
acquiring a first medical image set to be registered, wherein the first medical image set to be registered is a set of medical images shot by a first user in a medical visit process;
dividing the first to-be-registered medical image set into a first medical image subset based on medical image feature information;
acquiring a second medical image set used as a registration reference, wherein the second medical image set used as the registration reference is a set of medical images shot by the first user in another medical visit process;
dividing the second medical image set used as a registration reference into a second medical image subset based on the medical image feature information;
and taking any medical image subset in the second medical image set as a registration reference, and registering the medical image subset corresponding to any medical image subset in the first medical image set to be registered to obtain a registration result.
14. A computer readable medium having computer readable instructions stored thereon which are executable by a processor to implement the medical image registration method of any one of claims 1 to 11.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111664944.5A CN114299046A (en) | 2021-12-31 | 2021-12-31 | Medical image registration method, device, equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111664944.5A CN114299046A (en) | 2021-12-31 | 2021-12-31 | Medical image registration method, device, equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114299046A true CN114299046A (en) | 2022-04-08 |
Family
ID=80974014
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111664944.5A Pending CN114299046A (en) | 2021-12-31 | 2021-12-31 | Medical image registration method, device, equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114299046A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115953406A (en) * | 2023-03-14 | 2023-04-11 | 杭州太美星程医药科技有限公司 | Matching method, device, equipment and readable medium for medical image registration |
-
2021
- 2021-12-31 CN CN202111664944.5A patent/CN114299046A/en active Pending
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115953406A (en) * | 2023-03-14 | 2023-04-11 | 杭州太美星程医药科技有限公司 | Matching method, device, equipment and readable medium for medical image registration |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Nensa et al. | Artificial intelligence in nuclear medicine | |
| KR101898575B1 (en) | Method for predicting future state of progressive lesion and apparatus using the same | |
| US9047539B2 (en) | Medical workflow systems and methods with process workflow recordation | |
| US20120203575A1 (en) | Medical information system | |
| US20070133851A1 (en) | Method and apparatus for selecting computer-assisted algorithms based on protocol and/or parameters of an acquisistion system | |
| KR101885562B1 (en) | Method for mapping region of interest in first medical image onto second medical image and apparatus using the same | |
| KR101919847B1 (en) | Method for detecting automatically same regions of interest between images taken on a subject with temporal interval and apparatus using the same | |
| CN111080583A (en) | Medical image detection method, computer device and readable storage medium | |
| US10176569B2 (en) | Multiple algorithm lesion segmentation | |
| CN114299046A (en) | Medical image registration method, device, equipment and storage medium | |
| Aggarwal et al. | Developing and deploying deep learning models in brain magnetic resonance imaging: A review | |
| WO2017216356A1 (en) | System and method for viewing medical image | |
| JP7007469B2 (en) | Medical document creation support devices, methods and programs, trained models, and learning devices, methods and programs | |
| US11832955B2 (en) | Method and apparatus for providing information needed for dementia diagnosis | |
| Badr | Images in space and time: real big data in healthcare | |
| Fitzke et al. | Rapidread: Global deployment of state-of-the-art radiology AI for a large veterinary teleradiology practice | |
| US20170124290A1 (en) | Method and system for generating electronic medical reports | |
| Wang et al. | Preparing CT imaging datasets for deep learning in lung nodule analysis: Insights from four well-known datasets | |
| Helland et al. | Segmentation of glioblastomas in early post-operative multi-modal MRI with deep neural networks | |
| WO2017140133A1 (en) | System and method for medical imaging | |
| KR20190088371A (en) | Method for generating future image of progressive lesion and apparatus using the same | |
| Moreno et al. | Representation and indexing of medical images | |
| US10803593B2 (en) | Method and system for image compression | |
| US20230070906A1 (en) | Information processing apparatus, method, and program | |
| US20230401822A1 (en) | Systems and methods for medical image analysis and classification |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |