WO2016069086A1 - Imagerie thermique haute définition pour applications médicales - Google Patents

Imagerie thermique haute définition pour applications médicales Download PDF

Info

Publication number
WO2016069086A1
WO2016069086A1 PCT/US2015/044233 US2015044233W WO2016069086A1 WO 2016069086 A1 WO2016069086 A1 WO 2016069086A1 US 2015044233 W US2015044233 W US 2015044233W WO 2016069086 A1 WO2016069086 A1 WO 2016069086A1
Authority
WO
WIPO (PCT)
Prior art keywords
thermal
sensor
image processing
image
scene
Prior art date
Application number
PCT/US2015/044233
Other languages
English (en)
Inventor
John R. Franzini
Mark B. Lyles
Robert H. Murphy
Original Assignee
Bae Systems Information & Electronic Systems Integration Inc.
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Bae Systems Information & Electronic Systems Integration Inc. filed Critical Bae Systems Information & Electronic Systems Integration Inc.
Priority to EP15854988.1A priority Critical patent/EP3212064A4/fr
Priority to US15/109,140 priority patent/US10441177B2/en
Publication of WO2016069086A1 publication Critical patent/WO2016069086A1/fr

Links

Classifications

    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/48Other medical applications
    • A61B5/4887Locating particular structures in or on the body
    • A61B5/489Blood vessels
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/0059Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence
    • A61B5/0077Devices for viewing the surface of the body, e.g. camera, magnifying lens
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7203Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
    • A61B5/7217Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal of noise originating from a therapeutic or surgical apparatus, e.g. from a pacemaker
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235Details of waveform analysis
    • A61B5/725Details of waveform analysis using specific filters therefor, e.g. Kalman or adaptive filters
    • HELECTRICITY
    • H01ELECTRIC ELEMENTS
    • H01LSEMICONDUCTOR DEVICES NOT COVERED BY CLASS H10
    • H01L2924/00Indexing scheme for arrangements or methods for connecting or disconnecting semiconductor or solid-state bodies as covered by H01L24/00
    • H01L2924/30Technical effects
    • H01L2924/301Electrical effects
    • H01L2924/3025Electromagnetic shielding

Definitions

  • the present invention relates to high resolution IR imaging using the latest IR sensor technology combined with Real Time Image Processing algorithms. More particularly the invention relates to such imaging for medical applications.
  • Embodiments of the present disclosure provide a system and method for high definition thermal imaging and close focus viewing from 6 inches to an infinite distance in medical applications. Briefly described, in architecture, one embodiment of the system, among others, can be implemented as follows.
  • a device for high definition thermal imaging and close focus viewing from 6 inches to an infinite distance in medical applications includes a single channel uncooled thermal sensor with low noise characteristics and EMI shielding, a remote cable, and a laptop controller with enhanced real time image processing software.
  • the present disclosure can also be viewed as providing methods of providing a crisp, ultra-sharp, infrared image suitable for medical imaging in a hand carryable package.
  • one embodiment of such a method can be broadly summarized by the following steps: providing a portable, lightweight high- resolution infrared sensor; providing a housing for the infrared sensor, wherein the housing is EMI shielded; and using a processor, displaying an infrared image on a display screen coupled to the sensor.
  • Figure 1 is a perspective view of a preferred embodiment of the present invention
  • Figure 2 is an exploded view of high resolution IR sensor as shown in Figure l ;
  • Figure 3 is a diagrammatic illustration of the rear portion of the infrared sensor of Figure 1 showing two halves of the casing surrounding electronics, and other parts of the camera;
  • Figure 4 is a diagrammatic illustration of the two halves of the casing of
  • Figure 3 shown broken apart, with EMI shielding grooves that mate upon assembly providing for the required EMI shielding
  • Figure 5 is a diagrammatic illustration of the rear compartment of the housing for the camera of Figure 1 , illustrating EMI gaskets surrounding the apertures in the housing used for the interconnection of the camera to the laptop of Figure 1 ;
  • Figure 6 is a diagrammatic illustration of the EMI gaskets that are fitted into the appropriate orifices in the housing of Figure 5;
  • FIG. 7 is an example of Graphical User Interface (GUI) on a laptop computer
  • Figure 8 is an example of high resolution long wave IR output for vein detection
  • Figure 9 is an example of high resolution long wave IR output for hemorrhage detection
  • Figure 10 is an example of high resolution long wave IR output for bone temperature monitoring
  • Figure 11 is a flow schematic diagram of the infrared imaging system in which the infrared camera is coupled to a spatial band-pass filter, a scene -based noise suppression module, a pedestal subtraction unit and a thermal fusion image processing system, followed by unsharp masking to be able to exaggerate or enhance subsurface objects such as veins or bone burrs, in accordance with the first exemplary embodiment of the present disclosure;
  • Figure 12A is a diagrammatic illustration of real time full frame image processing for both low-frequency spatial noise removal and dynamic range enhancement, in accordance with the first exemplary embodiment of the present disclosure
  • Figure 12B is a diagrammatic illustration of real time full frame image processing for scene-based methods for high-frequency spatial noise removal including clutter, in accordance with the first exemplary embodiment of the present disclosure
  • Figure 13 is a flowchart showing method steps for removal of spatial noise, in accordance with the first exemplary embodiment of the present disclosure.
  • Figure 14 is a diagrammatic representation of the use of pedestal subtraction, thermal fusion and post processing to increase the contrast invisibility of small subsurface objects, in accordance with the first exemplary embodiment of the present disclosure.
  • the present invention is an apparatus for high resolution single channel thermal imaging in medical applications.
  • the apparatus includes some or all of the following: a highly sensitive EMI shielded thermal imaging device or focal plane array (FPA), a remote cable and laptop controller with real time image processing software. It provides a single viewable IR channel with a variable focus distance which can be optimized at any distance from six inches to infinity.
  • FPA focal plane array
  • the present invention enables high quality vision in the thermal band for greater awareness of everything within the field of view (FOV) from very close to distant objects and scenes.
  • FOV field of view
  • the sensor housing hereinafter the camera casing
  • the sensor housing is divided up into compartments with the joinder of the compartments being provided with EMI shielding therebetween in an annular ridge around the compartments.
  • EMI shielding for the rear compartment is provided to seal the connectors that exit the compartment against EMI interference.
  • the result is an improved infrared sensor which is lightweight, but nonetheless has sufficient EMI shielding to make possible the creation of ultra-sharp infrared images, especially on a laptop to which the sensor is coupled.
  • medical thermal image processing is accomplished by means of using a spatial bandpass and scene based noise suppression filtering, pedestal subtraction and thermal fusion image processing.
  • Prior art solutions apply a histogram based non-linear transfer function to the image globally or they may apply a variable linear gain and offset function locally. This solution enhances the medically relevant thermal scene information that is revealed to the user.
  • the system Due to the highly sensitive IR sensor and at 1 - 2 ft. of working distance, the system has an increased depth of field of (>6 inches), eliminating the need for autofocus motor controllers and associated complex control algorithms.
  • five preset filters are provided which are user selectable. The filters can be used individually or in combination and supply processed data in near real time (within 0.1 seconds). These image filters are available to the user via the laptop controller user interface.
  • the subject device can be used as an aid to Mohs surgery and similar dermatological skin treatments. Moreover, it may be used to discern live tissue from dead tissue in imaging and treatment of skin tags during plastic surgery. Likewise, the subject system can be used as a diagnostic aid during burn treatment such as differentiating between burn classifications. Moreover, the subject device may be used to detect the presence of abdominal aortic aneurysms. The device may also be used, for instance, during brain laser ablation treatment, with faster and more accurate thermal imaging of the dead tissue greatly enhancing the procedure.
  • the subject system may be utilized as an adjunctive aid in detecting cardiovascular issues including venal or arterial blockage, frostbite, inflammation, infection or sclerosis.
  • Figure 1 is a perspective view of a preferred embodiment of the present invention showing the high resolution IR imaging system. It consists of a 12 micron uncooled, low noise microbolometer focal plane array IR sensor 10, a laptop controller 12 and HDMI signal cable 14. These IR engine systems are based upon 12 micron pitch 640x480 Focal Plane Arrays (FPA). This smaller pitch enables more compact lens designs that provide improved thermal contrast. By adapting the systems for close focus high resolution thermal imaging, a great improvement in the technology and product offering was accomplished.
  • FPA Focal Plane Arrays
  • One aspect of the system design incorporates a single IR channel device which is fully enclosed within a dust/splash/EMI resistant container.
  • the IR sensor is powered up using the HDMI cable and has no user controls or interfaces, greatly simplifying the user interface.
  • a manual focus adjustment is provided at the objective lens for coarse adjustment. Due to the highly sensitive IR sensor and at 1 - 2 ft. of working distance, the system has an increased depth of field of (>6 inches), eliminating the need for autofocus motor controllers and associated complex control algorithms.
  • the IR engine systems described herein involve 12 micron pitch 640x480 Focal Plane Arrays (FPA). This smaller pitch enables more compact lens designs that provide improved thermal contrast. By adapting the systems for close focus high resolution thermal imaging, a great improvement in the technology was accomplished.
  • the subject system design incorporates a single IR channel device which is fully enclosed within a dust/splash/EMI resistant container.
  • the elimination of an autofocus motor controller is a major breakthrough and makes the unit smaller, lighter, more reliable and less expensive.
  • FIG 2 is an exploded view of the high resolution IR sensor as shown in Figure 1.
  • a camera lens 20 is carried by a front housing 22, which is in turn attached to an FPA assembly 24.
  • This assembly 24 is housed in a mid-housing 26, and a rear housing 28 with a mounting bracket 30, which is provided for convenience.
  • One of the major features of the subject invention is the EMI shielding that accompanies this very lightweight camera assembly. It will be appreciated that if there is any EMI or noise applied to the HMDI cable, what is presented on-screen is nothing more than a series of horizontal lines quite akin to what is presented on old- fashioned TVs with inadequate antenna systems. Thus, in order to provide a usable portable device, attention must be paid to the camera configuration.
  • the camera can be focused anywhere from 6 inches to infinity. This permits a lightweight camera to be transported anywhere within, for instance, a medical center and to be able to focus without autofocusing to any object within the focal range of the camera.
  • Features of the camera are as follows:
  • the laptop controller 12 ( Figure 1) provides a graphical user interface with up to five preset filters which are user selectable for image contrast enhancement.
  • An example of the graphical user output on the laptop computer is shown in Figure 7, in which camera 10 ( Figure 1) is focused on a human subject a couple of feet from the camera. Here the person being viewed by the subject system is clearly visible, where the detail of the individual's shirt is a testament to the sharpness of the IR image.
  • the laptop controller 12 is powered either by AC or remote battery, making the system truly portable.
  • the HDMI cable 14 is a standard interface needed for sensor power.
  • the housing utilized for the infrared sensor, with the sensor and the housing constituting a camera.
  • Figure 3 is a diagrammatic illustration of the rear portion of the infrared sensor of Figure 1 showing two halves of the casing surrounding electronics, and other parts of the camera.
  • Figure 4 is a diagrammatic illustration of the two halves of the casing of Figure 3 shown broken apart, with EMI shielding grooves that mate upon assembly providing for the required EMI shielding.
  • what is shown at 30 and 32 are the two halves of a rear facing housing which are secured together.
  • housing halves 30 and 32 are provided with EMI sealing grooves 33 containing EMI shielding material, which when the parts of the housing mate, provide for an EMI shield for the camera.
  • FIG. 5 is a diagrammatic illustration of the rear compartment of the housing for the camera 10 of Figure 1, illustrating EMI gaskets surrounding the apertures in the housing used for the interconnection of the camera 10 to the laptop 12 of Figure 1.
  • EMI shielding is further accomplished as illustrated in Figure 5 by providing a rear cap 34 to the rear of the camera housing, with the top and bottom views shown left and right in this diagram. With respect to the bottom view, apertures 35 are provided with recesses 36 adapted to receive EMI gaskets.
  • FIG 6 is a diagrammatic illustration of the EMI gaskets that are fitted into the appropriate orifices in the housing of Figure 5.
  • EMI gaskets 37 are configured as illustrated to fit into the corresponding recesses into the back cap of the camera housing. In this manner, a large portion of electromagnetic interference is removed from interfering with the rendition of the infrared image by the laptop computer.
  • Figure 7 is an example of Graphical User Interface (GUI) on a laptop computer.
  • GUI Graphical User Interface
  • the captured raw IR data is post processed with various suitable image processing algorithms to produce a number of LWIR movies as well as still images 32.
  • Figure 7 shows an example of a still image 32 after processing with the image processing algorithms.
  • the image processing is described in Figures 11- 14 hereinafter.
  • five preset filters are provided which are user selectable. The filters can be used individually or in combination and supply processed data in near real time (within 0.1 seconds). These image filters are available to the user via the laptop controller user interface.
  • the logic and description of the methods behind each preset filter is described hereinafter and is disclosed in the related PCT application PCT/US2014/060897 filed October 16, 2014.
  • Figure 8 is an example of high resolution long wave IR output for vein detection.
  • the following comparison images demonstrate significantly more pronounced venous structure of the arm with LWIR imaging over visible imagery.
  • the visible image 40 With the unprocessed image 42 and the processed image 44, it can be seen how little evidence exists of vein presence when viewed by the visible eye.
  • Unprocessed images refer to raw or original IR output from the FPA sensor.
  • Processsed images refer to the same original IR output except with real time image enhancement using the software resident on the laptop controller.
  • Figure 9 is an example of high resolution long wave IR output for hemorrhage detection. Referring to Figure 9 and during knee cap surgery, accidental nicking of blood vessels sometimes can occur. This causes the procedure to stop and the surgeon to have to irrigate the treatment, cauterize and restart the procedure. Using high resolution IR imagery, the procedure can be shortened due to increased visibility of the damaged blood vessel area as illustrated in unprocessed form at 50 and processed form at 52.
  • Figure 10 is an example of high resolution long wave IR output for bone temperature monitoring. Referring to Figure 10, the same can be said for bone marrow temperature monitoring as shown at 54 for the unprocessed image and at 56 for the processed image. Note the increased image quality of the IR image after image enhancement. Note also that bone temperature rises sharply in a deburring procedure as can be seen in the thermal image in Figure 10. The monitoring of potentially damaging excessive bone heating is possible through the use of the subject LWIR thermal imaging camera with image processing.
  • medical thermal image processing for vein, bone, or other subsurface element detection is accomplished by using a special bandpass and scene-based noise suppression filtering, pedestal subtraction, and thermal fusion image processing system. While prior art solutions apply a histogram-based, nonlinear transfer function to the image globally, or they may apply a variable linear gain and offset function locally, these solutions have not substantially enhanced the relevant thermal scene information revealed to the user.
  • an infrared camera output is coupled to a spatial band-pass filter having a band limitation such that the high-pass cut-on spatial frequency is equivalent to a radius of 6 to 60 pixels.
  • This configuration limits the input of spatial frequencies to the next step in the scene-based noise suppression system.
  • spatial noise removal is accomplished by measuring or estimating the spatial noise image contained within the original image followed by subtracting the spatial noise image from the original image.
  • the scene-based method is used to measure, estimate, or create, and then remove, spatial image noise from the real-time image sequence after an initial delay of a few seconds. After having removed spatial noise, one can consider pedestal subtraction.
  • Image dynamic range available to the human observer through a display is limited by many factors. Visual perception of a particular object in the scene is improved by utilizing as much of the available display dynamic range as is possible without degrading the dynamic range of other objects in the scene. Display dynamic range must thus be shared between many different scene components. To strike a proper balance, it is necessary to reduce the contrast of large and naturally high contrast scene elements prior to display in order to reserve display dynamic range for small but important scene elements that may be of low contrast in the scene.
  • Thermal fusion can also be used to emphasize subcutaneous objects.
  • thermal imagery can be viewed as having two types of scene information.
  • the first type of scene information is the size and shape of the various objects in the scene and the second type of scene information is temperature.
  • the captured 16-bit raw data is post processed with suitable image processing algorithms to produce a number of long- wavelength infrared (LWIR) movies as well as the images appearing herein.
  • LWIR long- wavelength infrared
  • the scene-based noise suppression system has a low spatial frequency noise removal system operating with a spatial band-pass filter frequency equivalent to a radius greater than 60 pixels and up to 480 pixels.
  • the combination of these spatial frequency filters increases the dynamic range and contrast for the objects of interest.
  • the scene-based noise suppression system also has a high-frequency fixed pattern, a slowly varying pattern, or a spatial noise removal system for the removal of unwanted image artifacts which degrade the visual experience of trying to resolve a vein or other subsurface features such as a bone.
  • the spatial band-pass filter in combination with the scene-based noise suppression provides a thermal image processing system that enhances and enables more efficient coupling to the human visual system of the observer of the thermal scene information.
  • Pedestal subtraction reduces the excess dynamic range of large naturally occurring high contrast scene elements, thus enabling smaller, low contrast and important scene elements such as veins to occupy a larger portion of the display dynamic range than would be possible without pedestal subtraction.
  • Further visualization of the subsurface structure may be provided by a fusion of enhanced thermal elements with non-enhanced thermal elements so as to provide a combined thermal fusion image processing system which utilizes the shape of the subsurface element and its relative temperature in order to be able to distinguish the particular subsurface artifact or structure.
  • a thermal fusion image processing system care is taken to keep all parts of the image out of saturation so that vein structure and bone structure can be easily viewed, not only for its position and shape but also for its color, all of which correlates to its temperature.
  • Unsharp masking may also be utilized in which the unsharp masking technique utilizes an unusually large radius of 7 to 70 pixels to enhance a wide range of medium to high-spatial frequency features that make the subsurface structures more visible and distinguishable from the low-frequency thermal background.
  • the processing involved in rendering the image incorporates a real-time full-frame rate system which involves a scene-based method for low- frequency spatial noise removal and dynamic range enhancement in which slowly varying or low-frequency image elements are removed by a spatial band-pass filter that removes the low spatial frequency image components.
  • the scene -based method for eliminating spatial or fixed pattern noise involves a method for eliminating high-frequency spatial or so-called fixed pattern noise, meaning noise and clutter removal, by removing a high spatial frequency filtered version of the image from the original image. This removal is done in one
  • a specialized algorithm for removal of the spatial image involves first creating a frame stack "SBN stack” by applying a 3 to 12 pixel radius spatial high pass filter to the previous two or more frames. Secondly, and in parallel, a frame stack "SBN mask stack” is created by thresholding the 3 to 12 pixel radius variance of each of the previous two or more frames. The next step is to remove the residual scene content from each frame in the stack by applying the "SBN mask stack” as a mask to each frame in the "SBN stack”. The result is "SBN masked stack.” The next step is to create a spatial noise reference image "SBNref image” by computing the stack frame average of the masked stack. The final step is the removal of the spatial noise from each subsequent frame by subtracting the "SBNref image” from each subsequent frame.
  • pedestal subtraction is utilized to preserve display dynamic range for small but important scene elements that may be of low contrast in the scene itself. This pedestal subtraction is done by reducing the contrast of large and naturally high contrast scene elements prior to display. The result is to preserve display high dynamic range for small but important scene elements that may be of low contrast.
  • thermal fusion is utilized to meld the size and shape of objects with their temperatures such that the combination of the two parameters heightens the visibility of the particular elements so that they may be visualized easily from the display.
  • post processing in one embodiment captures 16 bit raw data, linearly stretches the 16-bit data of a single frame, and both provides a 16 frame moving average filtration and at the same time increases subject contrast so as to be able to pop out or make more visible the subcutaneous object required.
  • thermal image processing systems utilize spatial band-pass and scene -based noise suppression filtering as well as pedestal subtraction, thermal fusion image processing and unsharp masking.
  • Figure 11 is a flow schematic diagram of the infrared imaging system in which the infrared camera is coupled to a spatial band-pass filter, a scene-based noise suppression module, a pedestal subtraction unit and a thermal fusion image processing system, followed by unsharp masking to be able to exaggerate or enhance subsurface objects such as veins or bone burrs.
  • Figure 11 schematically illustrates the infrared imaging system in which the infrared camera 114 is coupled to a spatial band-pass filter 122, a scene-based noise suppression module 124, a pedestal subtraction unit 126 and a thermal fusion image processing system 128, followed by unsharp masking to be able to exaggerate or enhance subsurface objects such as veins or bone burrs.
  • the thermal image processing system 120 takes the output of infrared camera 114 and couples it to a spatial band-pass filter 122 that is, in turn, coupled to a scene -based noise suppression unit 124.
  • the output of the scene -based noise suppression unit 124 is coupled to a pedestal subtraction module 126.
  • the pedestal subtraction unit 126 may be used to preserve as much of the available display dynamic range as possible by reducing contrast of large and naturally high contrast scene elements, thus to be able to visualize small low contrast scene elements.
  • the output of the pedestal subtraction module 126 is coupled to a thermal fusion image processing module 128.
  • the output of thermal fusion image processing module 128 is controlled at saturation controller 130 to keep all parts of the image out of saturation, such that veins or bone de-burring structures are visible, as indicated by boxes 132 and 134.
  • the resulting output of the thermal fusion image processing module 128 is passed through an unsharp masking module 136 to remove noncritical artifacts in the infrared camera output.
  • Unsharp masking module 136 is under control of control unit 137 which restricts the unsharp masking to using an unusually large radius of 120 pixels. Thereafter, the results are displayed on a display 139.
  • the scene -based noise suppression module 124 may include two different types of noise suppression systems.
  • the first type utilizes a low-frequency spatial noise removal system 150 in which spatial noise of a low-frequency nature is removed which simultaneously improves the dynamic range for those small indistinct subsurface elements of interest.
  • the second type of system used by the scene-based noise suppression module 124 is a scene-based high-frequency spatial noise removal module 152 which removes high-frequency spatial noise.
  • Figure 12A is a diagrammatic illustration of real time full frame image processing for both low-frequency spatial noise removal and dynamic range enhancement.
  • Figure 12B is a diagrammatic illustration of real time full frame image processing for scene-based methods for high-frequency spatial noise removal including clutter. While Figure 12A illustrates the real time full frame image processing for both low-frequency spatial noise removal and dynamic range enhancement, Figure 12B illustrates the basics of the real-time full-frame image processing available for scene-based noise suppression.
  • the scene-based method for low-frequency spatial noise removal and dynamic range enhancement starts off with slowly varying or low-frequency images within block 162.
  • the slowly varying or low-frequency images of block 162 may be applied to a spatial band-pass filter at block 164 to remove low-frequency spatial image components. As is shown in FIG.
  • the method provides for removal of high-frequency spatial elements to permit noise removal and thus clutter as well.
  • the method includes removal of high-frequency spatial image non-uniformity from the scene image at block 166.
  • the spatial noise image within the original image is measured or estimated.
  • the spatial noise is then subtracted from the original image.
  • spatial noise may refer to the slowly varying or temporarily fixed non-uniform images within the scene.
  • Figure 13 is a flowchart showing method steps for removal of spatial noise, in accordance with the first exemplary embodiment of the present disclosure.
  • the frame stack SBN stack is created by applying a 3 to 12 pixel radius spatial high pass filter to the first several hundred frames, as is shown at block 172.
  • the frame stack SBN mask stack is then created, in parallel, by applying a threshold to the 3 to 12 pixel radius variance of the first several hundred frames, as is shown at block 174.
  • the residual scene content from each frame in the stack SBN is removed by applying the stack SBN mask as a mask to each corresponding frame, as is shown at block 176.
  • the spatial noise reference image "SBNref ' is then created by computing the stack frame average of the masked SBN stack, as is shown at block 178. Spatial noise is then removed from each subsequent frame by subtracting the "SBNref image” from each frame in real time, as is shown at block 180.
  • FIG 14 is a diagrammatic representation of the use of pedesal subtraction, in which thermal fusion and post processing are used to increase the contrast visibility of small subsurface objects.
  • pedestal subtraction may allow displaying a high dynamic range for small, but important scene elements that may be of low contrast in the scene.
  • Pedestal subtraction may include reducing contrast of large and naturally high contrast scene elements prior to display, as is shown at block 182.
  • Reducing contrast may then allow for reserving a time result to display the high dynamic range for the small but important scene elements that may be of low contrast, as is shown at block 184.
  • two different types of information may be taken into account in order to display the subsurface object, as is shown at block 186.
  • the first type is the size or shape of the object as well as its location and the second type is its temperature.
  • 16 bit raw data may be captured.
  • the 16 bit data is linearly stretched corresponding to the stretching of a 16-bit data of a single frame.
  • a 16 frame moving average filtration may be used simultaneously with a system for increasing the contrast of the object sought after, as is shown at block 192 and block 194, respectively.
  • thermal imaging cameras can be used with enhanced techniques to be able to make visible various small and non-contrasted features that lie beneath the surface of the skin. All of the above is made possible by the use of EMI shielding in a specialized camera body or housing as described above.

Landscapes

  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • General Health & Medical Sciences (AREA)
  • Veterinary Medicine (AREA)
  • Biophysics (AREA)
  • Biomedical Technology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Medical Informatics (AREA)
  • Molecular Biology (AREA)
  • Surgery (AREA)
  • Animal Behavior & Ethology (AREA)
  • Physics & Mathematics (AREA)
  • Public Health (AREA)
  • Pathology (AREA)
  • Signal Processing (AREA)
  • Artificial Intelligence (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Physiology (AREA)
  • Psychiatry (AREA)
  • Vascular Medicine (AREA)
  • Studio Devices (AREA)
  • Transforming Light Signals Into Electric Signals (AREA)
  • Radiation Pyrometers (AREA)

Abstract

L'invention concerne un appareil pour une imagerie thermique haute résolution, dans le cadre d'applications médicales, qui possède un capteur protégé contre les interférences électromagnétiques (EMI) à canal unique, un câble à distance et un dispositif de commande pour ordinateur portable présentant un logiciel de traitement d'image en temps réel. L'appareil fournit des images infrarouge (IR) visibles en temps réel, haute résolution, à distance focale variable, pouvant être ajustée de six pouces à l'infini. La présente invention permet une imagerie claire et nette de la bande thermique pour une plus grande connaissance de tout ce qui se trouve à l'intérieur du champ de vision. L'invention concerne également diverses applications médicales qui pourraient bénéficier de l'imagerie thermique haute résolution.
PCT/US2015/044233 2013-07-23 2015-08-07 Imagerie thermique haute définition pour applications médicales WO2016069086A1 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
EP15854988.1A EP3212064A4 (fr) 2014-10-30 2015-08-07 Imagerie thermique haute définition pour applications médicales
US15/109,140 US10441177B2 (en) 2013-07-23 2015-08-07 High definition thermal imaging for medical applications

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US201462072557P 2014-10-30 2014-10-30
US62/072,557 2014-10-30

Publications (1)

Publication Number Publication Date
WO2016069086A1 true WO2016069086A1 (fr) 2016-05-06

Family

ID=55858142

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2015/044233 WO2016069086A1 (fr) 2013-07-23 2015-08-07 Imagerie thermique haute définition pour applications médicales

Country Status (2)

Country Link
EP (1) EP3212064A4 (fr)
WO (1) WO2016069086A1 (fr)

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050143662A1 (en) * 2000-05-03 2005-06-30 Rocky Mountain Biosystems, Inc. Optical imaging of subsurface anatomical structures and biomolecules
US20090212218A1 (en) * 2005-05-11 2009-08-27 Murata Manufacturing Co., Ltd. Infrared sensor
US20100041998A1 (en) * 2008-08-18 2010-02-18 Postel Olivier B Method for Detecting and/or Monitoring a Wound Using Infrared Thermal Imaging
US20130329054A1 (en) * 2011-06-10 2013-12-12 Flir Systems, Inc. Infrared camera system housing with metalized surface
US20140081133A1 (en) * 2009-12-15 2014-03-20 Emory University System and methods for providing real-time anatomical guidance in a diagnostic or therapeutic procedure

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20120037803A1 (en) * 2010-08-12 2012-02-16 Flir Systems, Inc. Electromagnetic interference shield
WO2015061128A1 (fr) * 2013-10-21 2015-04-30 Bae Systems Information And Electronic Systems Integration Inc. Traitement d'images thermiques médicales pour détection sous-cutanée des veines, des os et équivalent

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050143662A1 (en) * 2000-05-03 2005-06-30 Rocky Mountain Biosystems, Inc. Optical imaging of subsurface anatomical structures and biomolecules
US20090212218A1 (en) * 2005-05-11 2009-08-27 Murata Manufacturing Co., Ltd. Infrared sensor
US20100041998A1 (en) * 2008-08-18 2010-02-18 Postel Olivier B Method for Detecting and/or Monitoring a Wound Using Infrared Thermal Imaging
US20140081133A1 (en) * 2009-12-15 2014-03-20 Emory University System and methods for providing real-time anatomical guidance in a diagnostic or therapeutic procedure
US20130329054A1 (en) * 2011-06-10 2013-12-12 Flir Systems, Inc. Infrared camera system housing with metalized surface

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
See also references of EP3212064A4 *

Also Published As

Publication number Publication date
EP3212064A1 (fr) 2017-09-06
EP3212064A4 (fr) 2018-04-11

Similar Documents

Publication Publication Date Title
CN106796344B (zh) 锁定在感兴趣对象上的放大图像的系统、布置和方法
EP2876605B1 (fr) Masques de confidentialité de gradient
US8442355B2 (en) System and method for generating a multi-dimensional image
US9552629B2 (en) Medical thermal image processing for subcutaneous detection of veins, bones and the like
JP2006067521A (ja) 画像処理装置と方法、および画像撮像装置と方法
US20150363942A1 (en) Image processing device, endoscope apparatus, image processing method, and information storage device
US20160034787A1 (en) Detection device, learning device, detection method, learning method, and information storage device
Wieringa et al. Remote non-invasive stereoscopic imaging of blood vessels: first in-vivo results of a new multispectral contrast enhancement technology
KR20180100150A (ko) 광 레벨 적응 필터 및 방법
US20150257628A1 (en) Image processing device, information storage device, and image processing method
US10441177B2 (en) High definition thermal imaging for medical applications
JP2016173785A (ja) 診断装置並びに当該診断装置における画像処理方法及びそのプログラム
US20150363929A1 (en) Endoscope apparatus, image processing method, and information storage device
Shahadi et al. Eulerian video magnification: a review
CN111784686A (zh) 一种内窥镜出血区域的动态智能检测方法、系统及可读存储介质
CN109068035B (zh) 一种智能微相机阵列内窥成像系统
US9672596B2 (en) Image processing apparatus to generate a reduced image of an endoscopic image
CN109859148A (zh) 红外热图像处理方法及装置
EP3212064A1 (fr) Imagerie thermique haute définition pour applications médicales
Hsia et al. A 3D endoscopic imaging system with content-adaptive filtering and hierarchical similarity analysis
JPH01138876A (ja) カラー画像処理装置
Kanakatte et al. Surgical smoke dehazing and color reconstruction
US20170249734A1 (en) Automatic segmentation of breast tissue in a thermographic image
Fan et al. A new Eulerian temporal filtering method for boosting endoscopic video motion magnification
Noushad et al. Image Pair Fusion using Weighted Average Method

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 15854988

Country of ref document: EP

Kind code of ref document: A1

WWE Wipo information: entry into national phase

Ref document number: 15109140

Country of ref document: US

NENP Non-entry into the national phase

Ref country code: DE

REEP Request for entry into the european phase

Ref document number: 2015854988

Country of ref document: EP