Method and apparatus for temperature measurement using magnetic resonance imaging

Abstract

A system and method for analyzing image data. The image data can be used to help determine the presence of features in an image. The features can include bubbles.

Description

Technical Field

[0001] The present teachings relate generally to imaging analysis methods and systems, and in particular to a method and system for bubble determination. Background Art

[0002] The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.

[0003] Imaging techniques have been used to image various parts of the human anatomy. Imaging techniques include ionizing radiation, generating fields relative to the human anatomy, and the like. Various types of imaging include imaging by generating a field relative to the anatomy, such as a magnetic field (e.g., a magnetic resonance imager (MRI)) and sensing changes in atomic particles of the anatomy caused by the field. Determining the temperature within the image is performed using various techniques, such as in Those technologies used in laser ablation systems include the MRI-guided minimally invasive laser ablation system sold by Medtronic, Inc., with a place of business in Minnesota, USA. Summary of the invention

[0004] During various surgeries, treatment can be applied to a subject. The subject can include a non-living structure or system, such as a fuselage or other structure. Additionally or alternatively, the subject can include a living subject, such as a human subject. Regardless, in various embodiments, the apparatus can be used to apply treatment to the subject. The treatment can include applying a heat source or generating heat at a selected location within the subject.

[0005] During the application of heat, a selected treatment, such as ablation, may be performed. Ablation may occur within a subject, such as to destroy or remove selected tissue, such as a tumor. In various embodiments, an ablation instrument may be located within the subject's brain to destroy a tumor therein.

[0006] The heat application catheter can be located within the subject. For example, a cold laser fiber (CLF) system can be used to deliver thermal energy to tissue. Such CLF systems include those disclosed in U.S. Patent No. 7,270,656, which is incorporated herein by reference. The CLF can be used to deliver thermal energy to a selected portion of a subject to excise tissue within the subject. During excision, it is selected to determine the temperature near the excision instrument at a selected line of sight within the subject. In various embodiments, an image of the subject can be acquired to calculate or determine the temperature within the subject, the image including an area within or near the excision instrument.

[0007] When acquiring an image of a subject, various items within the image may cause variations in the determined temperature. For example, bubbles may form in a subject during a resection procedure. During a resection procedure, the formation of bubbles may allow or require the temperature of the bubble area and / or the area near the bubble to be determined. The bubbles and phase shifts in a selected image modality (e.g., magnetic resonance imaging) may produce distortions or artifacts that may be taken into account to determine the selected temperature. Therefore, a system and method for detecting and / or correcting phase distortion caused by bubbles to determine the temperature at a selected location within an image is disclosed. The selected location may include the location of a resection instrument.

[0008] Further areas of applicability will become apparent from the description provided herein.It should be understood that the description and specific examples are intended for purposes of illustration only and are not intended to limit the scope of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The drawings described herein are for illustration purposes only and are not intended to limit the scope of the present disclosure in any way.

[0010] Figure 1 is an environmental view of a kit including a surgical navigation system and / or an imaging system and / or a resection system in various embodiments according to various embodiments;

[0011] Figure 2 is a schematic diagram of a subject and an apparatus positioned relative to the subject according to various embodiments;

[0012] Figure 3A are exemplary images of a subject with an instrument located within its tissue according to various embodiments;

[0013] Figure 3B is an image of a subject having an instrument therein, with a low intensity region near the instrument;

[0014] Figure 4 is a flow chart of a method for determining bubbles and / or compensating therefor;

[0015] Figure 5 is a detailed flow chart of the method for generating a bubble image library;

[0016] Figure 6 is an instance of a bubble image in the bubble image library;

[0017] Figure 7 is a schematic diagram of comparison and identification according to various embodiments;

[0018] Figure 8 is a schematic diagram of a comparison method according to various embodiments;

[0019] Fig. 9It is described in detail according to various embodiments Figure 4 Flow chart of the bubble detection and compensation method;

[0020] Fig.10 is a flow chart detailing a method for determining a region of interest according to various embodiments;

[0021] Fig.11 is a flowchart illustrating a method for determining bubbles in an image according to various embodiments; and

[0022] Fig.12 yes Fig.11 An exemplary application of the method depicted in the flow chart of FIG. DETAILED DESCRIPTION

[0023] The following description is merely exemplary in nature and is not intended to limit the present disclosure, application, or uses.

[0024] refer to Figure 1 In various embodiments, a surgery may be performed using a navigation system 20. The surgery may be any appropriate surgery, such as resection surgery, neurosurgery, spinal surgery, and orthopedic surgery. The navigation system 20 may include various components as will be discussed further herein. The navigation system 20 may allow a user 25, such as a surgeon, to view the position of an instrument 24 relative to a coordinate system on a display 22. The coordinate system may be formed relative to an image, such as in image-guided surgery, or the coordinate system may simply be registered to the patient, such as in image-free surgery.

[0025] As further discussed herein, image data may be used or used to assist in performing surgery. The image data may be image data acquired from a patient 28 using any suitable imaging system such as a magnetic resonance imaging (MRI) system 26. The MRI imaging system 26 may be used to acquire selected image data and / or other types of data, such as diffusion data associated with the patient 28. The image data of the subject 28 may include selected types of data, including amplitude and phase data. Various types of data may be used to generate images for viewing on the display 22. The image data may be used by a user or surgeon 25, such as during a selected surgery, whether or not it is a navigational surgery. The navigation and imaging systems may include those disclosed in U.S. Pat. No. 8,340,376, issued Dec. 25, 2012, which is incorporated herein by reference in its entirety.

[0026] In various embodiments, subject 28 can be a human patient. However, it should be understood that subject 28 need not be a human. In addition, the subject need not be a living subject. It should be understood that various structural systems (e.g., fuselages, test systems, mainframe computers, etc.). Therefore, those skilled in the art should understand that the present disclosure is not limited to only human subjects.

[0027] Navigation system 20 can be used to navigate or track instruments, including: catheters (e.g., ablation and / or delivery), probes, needles, guidewires, instruments, implants, deep brain stimulators, electrical leads, etc. Instruments 24 can be used in any area of ​​the body. Likewise, any appropriate information about instruments 24 can be displayed on display 22 for surgeon 25 to view.

[0028] Although the navigation system 20 may include an exemplary imaging device 26, those skilled in the art will appreciate that the discussion of the imaging device 26 is for understanding of the present discussion only, and any suitable imaging system, navigation system, patient-specific data, and non-patient-specific data may be used. The image data may be captured or obtained with any suitable device at any suitable time.

[0029] The navigation system 20 may include an optional imaging device 26 for acquiring preoperative, intraoperative, or postoperative or real-time image data of a patient 28. The depicted imaging device 26 may be, for example, a magnetic resonance imaging device (MRI). Other imaging devices may include an x-ray C-arm having an x-ray source and an x-ray receiving portion, a computed tomography system, Imaging System, etc. An imaging device 26 may be provided to acquire image data of the patient 28 prior to or during a procedure to diagnose the patient 28 .

[0030] although Figure 1 An environmental view is depicted showing the patient, surgeon, navigation system, and other elements, but it should be understood that this is merely an example of all the parts that may be provided together. For example, an electromagnetic navigation or tracking system may not be provided in the room with the imaging MRI system 26, but rather in a room with the imaging MRI system 26. Figure 1 The diagram is shown for illustration purposes and may be separated for use in actual procedures.

[0031] The imaging device controller 34 can control the imaging device 26 to capture and store image data for use, such as real-time or later use. The controller 34 can also be separate from the imaging device 26. Moreover, the controller 34 can be used to control and obtain image data of the patient 28 during or before surgery.

[0032] The image data may then be forwarded from the controller 34 to the processor system 40 via the communication system 41. The communication system 41 may be wireless, wired, a data transfer device (e.g., a CD-Rom or DVD-Rom), or any suitable system. The station 42 may be a workstation and may include the processor system 40, the display 22, the user interface 44, and the memory 46. It should also be understood that the image data need not first be retained in the controller 34, but may be transmitted directly to the workstation 42 or to the tracking system 50, as discussed herein.

[0033] The workstation 42 provides facilities for displaying image data as images on the display 22, saving, manipulating in digital form, or printing hard copy images of the received image data. A user interface 44 allows a physician or user to provide input via the controller 34 to control the imaging device 26 or adjust the display settings of the display 22, and the user interface may be a keyboard, mouse, stylus, touch screen, or other suitable device.

[0034] The processor system 40 may process various types of data, such as image data, provided in the memory 46 or from the imaging system 26. The processor system 40 may also process navigation information, such as information provided from the tracking system 50. In addition, the navigation processing may include determining the position (e.g., three degrees of freedom rotation and three degrees of freedom spatial position) of the tracked instrument relative to the patient 28 to be displayed on the display 22 relative to the image data 23. As discussed herein, the processor system 40 may perform / execute instructions to perform various types of analysis, such as temperature determination, position determination, etc. It should be understood that each of the processing portions may be processed by a separate or single processor, or may be processed substantially sequentially with an appropriate processor.

[0035] The optional imaging device 26 may be any suitable 2D, 3D or time-varying imaging modality. For example, isocentric fluoroscopy, biplane fluoroscopy, Imaging devices (i.e., devices sold by Medtronic, Inc., with a place of business in Minnesota, USA), ultrasound, computed tomography (CT), T1-weighted magnetic resonance imaging (MRI), T2-weighted MRI, positron emission tomography (PET), optical coherence tomography (OCT), single photon emission computed tomography (SPECT), or planar gamma scintigraphy (PGS).

[0036] The image data obtained from the patient 28 can be used for various purposes. As discussed herein, the image data can be obtained for performing navigational surgery on an anatomical structure, planning an operation or surgery on an anatomical structure, and other appropriate reasons. For example, during a neurological surgery, it can be selected to obtain image data of the brain of the patient 28 for viewing during surgery, and in various embodiments, determine the temperature near a selected portion of the instrument and / or navigate the instrument 24 relative to the image data 23. In addition, the acquired image data can be used to plan the movement of the instrument 24 or for positioning an implant during surgery.

[0037] Imaging device 26 may also be used to obtain various types of data other than just image data. Various types of data may be used and superimposed one on another to obtain an appropriate image of the anatomical structure. For example, a magnetic resonance image of a portion of patient 28, such as brain 29, may be obtained for viewing in a selected manner. For example, a 3-D model of the brain may be formed based on multiple slices of MRI data for display on display 22 during tracking for a navigated procedure.

[0038] Briefly, the navigation system 20 operates to determine the position of the instrument 24 relative to the subject 28 and is used for viewing the image 23 relative to the subject 28, as discussed herein. The navigation system 20 creates (manually or automatically) a translation mapping between all points in the image data or image space and corresponding points in the patient's anatomy in the patient space, and an exemplary 2D to 3D registration procedure is described in U.S. Patent No. 7,570,791, entitled "Method and Apparatus for Performing 2D to 3D Registration," issued on August 4, 2009, which is hereby incorporated by reference in its entirety. The selected points may be fiducial markers 69 comprising anatomical or artificial landmarks, such as those described in U.S. Pat. No. 6,381,485, entitled "Registration of Human Anatomy Integrated for Electromagnetic Localization," issued on April 30, 2002, which is hereby incorporated by reference in its entirety. After establishing the mapping, the image space and patient space are registered, which mapping may occur and be determined or selected in both image space and subject space. In other words, registration is the procedure of determining how positions in image space are related to corresponding points in real or patient space. This may also be used to plot the position of the instrument 24 relative to a proposed trajectory and / or determined anatomical target. Registration may occur by a process and / or system such as that disclosed in U.S. Pat. No. RE42,226, issued on March 15, 2011, entitled "PERCUTANEOUS REGISTRATION APPARATUS AND METHOD FOR USE IN COMPUTER-ASSISTED SURGICAL NAVIGATION," which is incorporated herein by reference in its entirety. In various embodiments, registration may include 2D to 3D registration, such as the exemplary 2D to 3D registration procedure set forth in U.S. Serial No. 10 / 644,680, filed on August 20, 2003, which is hereby incorporated herein by reference in its entirety, which is now U.S. Pat. No. 7,570,791, issued on August 4, 2009, entitled "Method and Apparatus for Performing 2D to 3D Registration."

[0039] Continue to refer Figure 1 , the navigation system 20 may further include a tracking system 50, which includes one or more locators, such as an electromagnetic (EM) locator 52 (e.g., which may also be referred to as a transmitter array, a tracking array, a tracking coil or a coil array, and may include a transmitter and / or a receiver coil array). It should be understood that other suitable locators, such as optical locators, may also be provided or used. Different locators may operate in different modes such as optical fields or magnetic fields, radar, etc. The tracking system 50 is understood to be not limited to any particular tracking system modality, such as EM, optical, acoustic, etc. Any suitable tracking system modality according to the present disclosure may be used. In addition, any tracked instrument such as the instrument 24 and / or the dynamic reference frame (DRF) 58 may include one or more tracking devices operating in one or more tracking modes. Therefore, the tracking system 50 may be selected as any suitable tracking system, including providing optical and AxiEM TM Electromagnetic tracking option Surgical navigation system.

[0040] Those skilled in the art will appreciate that the coil array 52 can transmit or receive, and thus referring to the coil array 52 as a transmitter or a transmitting coil array is exemplary and non-limiting herein. The tracking system 50 may further include a coil array controller (CAC) 54, which may have at least one navigation interface or navigation device interface (NDI) 56 for connecting an instrument tracking device 67 of the locator 52, on or associated with the instrument 24, and a dynamic reference system 58. If selected, the coil array controller 54 and at least one navigation interface 56 may be disposed in a single relatively small CAC / NDI container. The instrument tracking device 67 may be placed or associated with the instrument 24 in any suitable manner or position to allow a selected portion (e.g., a terminal) of the instrument 24 to be determined. In various embodiments, the tracking device 67 may include a coil located at or near the terminal of the instrument 24.

[0041] In the optional optical system, the optical positioner typically includes one or more cameras that "view" the subject space. The camera can be used to determine the position of the tracking element relative to the camera. The tracking device includes a component that can be viewed by the camera. The optical tracking device can include one or more passive or active parts. Active tracking devices can emit visible wavelengths, including infrared wavelengths. Passive tracking devices can reflect selected wavelengths, including infrared wavelengths.

[0042] The tracking system may be included in the navigation system 20, and in various embodiments may include an EM localizer, which may be a coil array 52. ​​The EM localizer 52 may include an EM localizer described in the following patents: No. 7,751,865, entitled "METHOD AND APPARATUS FOR SURGICAL NAVIGATION", issued on July 6, 2010; U.S. Patent No. 5,913,820, entitled "Position Location System", issued on June 22, 1999; and U.S. Patent No. 5,592,939, entitled "Method and System for Navigating a Catheter Probe", issued on January 14, 1997, each of which is hereby incorporated by reference in its entirety. The localizer may also be supplemented and / or replaced with an additional or alternative localizer. It will be appreciated that, according to any of the various embodiments, the localizer 52 can transmit signals that are received by the dynamic reference frame 58 and a tracking device associated with (e.g., connected to) the instrument 24. The dynamic reference frame 58 and the tracking device can then transmit signals based on the signals of the generated field received / sensed from one or more of the localizers 52. A tracking system that includes an optical tracking system can include a tracking system sold by Medtronic Navigation. Surgical Navigation System. The optical localizer can view the subject space and the tracking devices associated with the DRF 58 and / or the instrument 24.

[0043] Alone or in combination with other suitable processor systems including the coil array controller 54 and the controller 34, the workstation 42 can identify corresponding points on a pre-acquired image or atlas model relative to the tracked instrument 24 and display the position relative to the image data 23 on the display 22. This identification is called navigation or positioning. Icons representing local points or instruments are shown in several two-dimensional image planes on the display 22 and on three-dimensional (3D) images and models. To maintain registration accuracy, the navigation system 20 can continuously track the position of the patient 28 using a dynamic reference system 58. The position of the instrument 24 can be transmitted from the instrument tracking device 67 via a communication system such as wired or wireless communication. The tracking device or any other suitable part can use a wireless communication channel instead of coupling with a physical transmission line, and the wireless communication channel is disclosed in U.S. Patent No. 6,474,341, entitled "Surgical Communication Power System", issued on November 5, 2002, which is incorporated herein by reference in its entirety.

[0044] The instrument 24 used in the procedure can be any suitable instrument (e.g., a catheter, a probe, a guide, etc.) and can be used for a variety of procedures and methods, such as delivering material, ablating energy (e.g., heat), or providing electrical stimulation to a selected portion of a patient 28 (such as within a brain 29). The material can be any suitable material, such as a bioactive material, a pharmacological material, a contrast agent, or any suitable material. As further discussed herein, the instrument 24 can be precisely positioned via the navigation system 20 and further used to implement a protocol for positioning and / or applying treatment relative to the patient 28 in any suitable manner, such as within the brain 29. The instrument 24 can also include a brain probe to perform deep brain stimulation and / or ablation.

[0045] refer to Figure 2 , the instrument 24 can be positioned within the brain 29 of the subject 28, for example, such as various techniques, such as those disclosed in U.S. Pat. No. 7,270,656, which is incorporated herein by reference. In addition, the instrument 24 can include various features, such as an energy delivery or transmission system or mechanism 100, which can include a fiber optic cable to transmit laser energy to the distal end 104 of the instrument. The distal end 104 of the fiber optic member 100 can be near the terminal 110 of the instrument 24. Therefore, the instrument 24 can generate heat or thermal energy in the subject 28, such as near a tumor 114 in the brain 29. The temperature near the terminal 110, such as within the tumor 114, can be adjusted by providing or changing the amount of energy through the energy transmission system 100 and / or transmitting or passing a cooling medium through the instrument 24. Transmitting a cooling medium can include providing a cooling medium to a cooling medium inlet 120, which can pass through a cooling medium loop 124. The cooling medium can be any suitable material, such as water, saline, etc. However, thermal energy may be delivered to subject 28 to perform treatment on tumor 114 in subject 28. During treatment of subject 28, imaging system 26 may be used to image subject 28 to determine the temperature at or near tip 104 and / or terminal 110.

[0046] As discussed above, the instrument 24 can be tracked relative to the subject 28 so that the position of the distal end 110 and / or the tip of the energy delivery system 100 can be determined. Thus, images acquired using the imaging system 26 can be registered to the subject 28 and / or the instrument 24. This allows the navigational position of the instrument 24 to be determined relative to the images acquired from the subject 28. The position of the instrument 24 can be displayed on the display device 22, such as in a graphical representation 24i' displayed on the display system 22, such as superimposed on the image 23.

[0047] During resection surgery, if Figure 1As shown in FIG. 1 , user 25 can apply energy to subject 28 with instrument 24 at a selected rate or time to heat a portion of the subject. During heating, heating images are acquired at a selected rate. For example, heating images can be acquired at a rate of about every five seconds, every ten seconds, or any selected time period. Thus, during the application of thermal energy to subject 28, thermal images are acquired to determine the temperature at the instrument location within subject 28.

[0048] A thermal image may be an image acquired with imaging system 26 for determining temperature within subject 28. A thermal image may contain various information, such as diffusion information or relaxation times, or may be analyzed to determine a phase change in temperature and / or temperature change from a previous thermal image. Thus, a thermal image may be used to determine temperature or temperature change relative to a previous image or on a pixel or voxel basis alone. Thus, a thermal image may include an image acquired from subject 28 for determining temperature therein.

[0049] The thermal image may be displayed on the display 22, or other suitable display. For example, the thermal image may be displayed on the display device 22, as shown in FIG. 3. The thermal image may include a first thermal image 150. The first thermal image may include an image of the brain 29 as the image 23. The thermal image 150 may also include image data or an image of the instrument 24 as the instrument 24a. It should be understood that based on the details of the instrument 24, the instrument 24 may be presented in different shapes or geometric shapes, and in Figure 3A The illustration of one or more legs in the first thermal image 150 is merely exemplary. However, the thermal image 150 can be displayed for viewing by the user 25 to roughly show the amplitude in the image. The thermal image 150 can be a slice, such as an MRI image slice, where each voxel or pixel contains an intensity, where higher intensities are lighter colors and lower intensities are darker colors. The first thermal image 150 can be a baseline or first heated image. Therefore, in various embodiments, a second heated image can be acquired.

[0050] refer to Figure 3B , a second thermal image 160 is shown. The thermal image 160 may also depict the instrument 24a. A dark area or low intensity area 166 is near or adjacent to the instrument 24a. The low intensity area 166 may be a bubble formed near or adjacent to the instrument 24 within the subject 28. The low intensity area 166 may appear in the thermal image 160 as a dark or low intensity portion near the instrument 24a. However, it may be difficult to identify the low intensity area 166 as a bubble by simply viewing the display device 22. In addition, even if the low intensity area 166 is present, the temperature at the portion containing the bubble or low intensity area 166 may be calculated, as discussed further herein.

[0051] Without being limited by theory, bubbles may be caused by heat generated in various tissues or materials. The material may cause gas to form within a certain volume. The volume may be defined by the material in which the instrument 24 is placed. Therefore, bubbles in anatomical structures may be caused by various local conditions therein. In images such as MRI images, as discussed herein, bubbles may be areas with no significant signal due to low proton density and / or rapid motion, which are surrounded by image phase / frequency disturbances caused by differences in magnetic susceptibility between adjacent tissues and the bubble volume. Bubbles in this context may appear due to conditions associated with a selected treatment of the subject, such as heat. The specific size and composition of a given bubble depends on the local environment (e.g., tissue) and the treatment (e.g., heating) conditions.

[0052] As further discussed herein, the first thermal image 150 may be acquired at any time during the application of thermal energy to the subject 28. Additionally, the second thermal image 160 may be any subsequent image, such as the image immediately following it, and may also be referred to as a current thermal image. Thus, thermal images may be acquired sequentially during the application of thermal energy to the subject. Each thermal image acquired that does not contain bubbles may be a first or baseline image, and a subsequent image that contains bubbles, such as the image immediately following it, may be a second thermal image 160. However, it should be understood that the baseline or first thermal image 150 may also be an initial image acquired from the subject 28. In various embodiments, the first thermal image 150 may always be the first or baseline image, and each subsequent image may be compared thereto for use in determining and / or helping to determine the presence of bubbles in the image.

[0053] As discussed above, reference Figure 3A and Figure 3B , dark areas or artifacts 166 may appear in the thermal image 160. Area points 166 may be bubbles or other artifact features that may reduce the confidence in the temperature determined using the thermal image 160. Therefore, referring to Figure 4 , depicting a bubble determination and / or compensation method 180. The bubble detection and / or compensation method 180 may include multiple steps or procedures, which may be included in various sub-steps or procedures as further discussed herein, but begin in start block 182. Thus, the method 180 may be understood as an overall or inclusive method or algorithm for detecting and / or compensating for bubbles in thermal images, which may include various sub-routines or elements including more than one step as discussed herein. Furthermore, it should be understood that the method 180 may be implemented as instructions executed by a selected processor system, such as the processor system 40. The method 180 may be performed substantially automatically when a selected thermal image or comparison image is accessed or acquired.

[0054] First, a bubble image library may be generated in block 188. The detection and compensation method 180 may not require the generation of a bubble image library, but may include the generation of a bubble image library for clarity and completeness of the current discussion. Thus, as discussed above, the library may be generated, such as in real time and / or prior to performing a selected procedure, such as a resection procedure.

[0055] Regardless of whether the bubble library was generated immediately before or at a previous time, the bubble image library can be accessed in box 194. Therefore, the bubble image library 188 can be stored on or in a selected memory system for access by a processor, such as the processor system 40 discussed above. It should be understood that the processor system 40 can include multiple processors, and the detection and compensation method 180 can be performed by a processor included in the processor system 40, separated from the processor system, and / or in communication with the processor system. In any case, in box 194, the appropriate processor can execute instructions to access the bubble image library. The bubble image library accessed in box 194 can contain appropriate bubble images, which can be based on the selected model used to generate the bubble library in box 188. The bubble image library accessed in box 194 can contain more than one type of image, such as amplitude and / or phase data. The bubble image library access in box 194 can include a magnetic resonance imaging system or be generated based on a magnetic resonance imaging system.

[0056] In block 194, the bubble image library may be accessed at any suitable time. The bubble image library is depicted in method 180 as being accessed first, however, the bubble image library need not be accessed prior to comparison with the selected image, such as during comparison or prior to comparing a bubble image from the bubble image library with the selected image, as discussed further herein.

[0057] Regardless of the timing of accessing the bubble library in box 194, accessing the current thermal image in box 198 may occur. The current thermal image accessed in box 198 may be a thermal image acquired by the user 25 or under the guidance of the user during a selected procedure. The current thermal image is acquired in an attempt to determine the temperature within the subject 28 relative to the instrument 24 at or near the resection area of ​​the subject. As discussed above, the current thermal image can be used to determine the current temperature or the temperature when the thermal image was acquired. Typically, a rate may be selected, such as acquiring the current thermal image five seconds after the immediately preceding thermal image. However, it should be understood that the current thermal image may be acquired at any appropriate time relative to the previous thermal image, which may be selected by the user 25.

[0058] Accessing a previous thermal image in box 202 may also occur. The previous thermal image may be any suitable previous thermal image, such as the immediately previous thermal image and / or any thermal image acquired prior to the current thermal image. For example, during various surgeries, an initial or pre-resection thermal image may be acquired from subject 28. The previous thermal image may be a thermal image acquired at the time of the first resection or treatment or prior to the resection or treatment. However, in various embodiments, the previous thermal image may be a thermal image acquired immediately prior to accessing the current thermal image in box 198.

[0059] Regardless of the timing of collection of the current thermal image and the previous thermal image, the two accessed thermal images may be compared in box 210. Comparing the current thermal image with the previous thermal image in box 210 may be used to generate a comparison image. The comparison image may be generated in any suitable manner, as further discussed herein. The generation of the comparison image may attempt to determine the differences between the current thermal image and the previous thermal image. The differences may include amplitude and / or phase differences between the current thermal image and the previous thermal image. The generated comparison image may include these differences for further analysis, which is also discussed herein.

[0060] The generated comparison image can then be analyzed to determine whether bubbles exist or may exist in the comparison image. In various embodiments, in box 220, the comparison image can be compared with at least one bubble image accessed from a bubble image library and then the generated comparison image. The comparison of the at least one bubble image with the generated comparison image can be completed in any appropriate manner, as discussed herein. For example, the accessed bubble image library can contain bubble images that contain amplitude information and / or phase changes or drifts that may be caused by the presence of bubbles. When the bubble image from the accessed bubble image library is compared with the generated comparison image in box 220, it can be determined in box 230 whether bubbles exist in the comparison image. As further discussed herein, determining whether bubbles exist in the generated comparison image can be based on a comparison of bubble images from the bubble image library. In various embodiments, the comparison image can also be analyzed or compared in a heuristic manner, such as using a selected system to analyze the image, as discussed herein.

[0061] A determination may be made in box 230 whether bubbles are present based on the comparison in box 220. If bubbles are not present, then in box 198, NO path 234 may be followed to access a current thermal image. Likewise, accessing the current thermal image in box 198 may be performed at any appropriate time and may be a current thermal image subsequent to the thermal image that may be accessed in the first iteration. Thus, it should be understood that method 180 may be an iterative process that may be performed during a selected procedure, such as during a resection procedure on subject 28. The current thermal image accessed in box 198 may be any appropriate current thermal image and may be at a time between the start of treatment and the termination of treatment and any appropriate intermediate point therebetween.

[0062] If it is determined in box 230 that bubbles are present, then a YES path 238 may be followed. The YES path 238 may be followed to identify the location of the bubble comparison image in box 244. Identifying the location of the bubble in the comparison image in box 244 may include identifying the bubble in the comparison image for further analysis and determination of the current thermal image or the generated comparison image. Identifying the bubble location in box 244 may include identifying the presence of bubbles and / or the generated comparison image and / or accessing pixels or voxels in the current thermal image that belong to bubbles and / or are affected by bubbles. Therefore, if selected, identifying the location of the bubble in the comparison image may allow for further compensation for the presence of bubbles in the current thermal image.

[0063] Thus, after identifying the bubble location in block 244, compensation determination block 248 allows for a determination as to whether compensation will occur. As discussed herein, user 25 may choose to compensate temperature determinations for the identified location of the bubble and / or may determine to terminate treatment for a selected period of time to allow the bubble to dissipate.

[0064] Thus, the compensation determination in block 248 may allow the user to determine not to compensate and follow the NO path 252 to perform various selected procedures. Additionally, while following the NO path 252, the method 180 may iterate, as noted herein. Furthermore, only bubbles may be identified in the image and identified to the user 25. The identity of the user may be displayed with and / or separately from the image 23. Thus, in various embodiments, the method 180 may only identify bubbles or possible bubbles.

[0065] When following the NO path 252, various other procedures or steps may occur. For example, the procedure is paused in the optional pause box 256. After pausing the procedure for a selected period of time (e.g., about one second to about one minute, or any suitable time) in the pause box 256, the user 25 and / or the ablation system may again access the current thermal image in box 198. Likewise, the current thermal image accessed in box 198 may be acquired after the previous current image in box 198, such as after the pause 256. Likewise, it may be determined in box 248 whether bubbles exist in a thermal image or the current thermal image and whether compensation is to be performed. Thus, if compensation is not to be performed, identifying bubbles and the current thermal image may allow the user 25 to pause or allow the bubbles to dissipate. However, the system performing the method 180 may be used to automatically identify whether bubbles exist within the current thermal image based on the algorithm method 180.

[0066] The compensation determination in box 248 also allows compensation to occur, so a YES path 260 can be followed. If compensation is selected in box 248, a YES path 260 can be followed to remove distortion / artifacts caused by bubbles in the current thermal image and / or other selected images, such as the generated compensated image, in box 270. Removing distortion or artifacts caused by bubbles in the current thermal image in box 270 can be performed according to selected techniques, including those discussed further herein, such as removing phase distortion and / or amplitude distortion caused by the identified bubbles at the identified locations. The compensated image generated in box 270 can include distortion or artifacts removed, such as by subtracting the identified bubbles.

[0067] Once the distortion is removed in block 270, the temperature in the compensated image may be determined in block 274. The temperature determined in block 274 may be used to perform a selected procedure, such as determining a temperature at or near the tip of instrument 24. As discussed above, when a selected temperature is reached or attempted to be reached, a resection procedure may occur or be performed. Thus, as discussed herein, determining the temperature in the compensated image in block 274 may be used to perform a procedure, such as a resection procedure, on subject 28.

[0068] Then, in block 278, the determined temperature in the compensated image may determine whether the procedure may proceed based on selected criteria (e.g., temperature, duration, etc.) However, the determination of whether to proceed with the procedure in block 278 may be selected again based on the user 25 and / or the performance of the selected procedure including the resection procedure.

[0069] If it is determined that the process will continue, the YES path 282 can be followed. In box 198, the YES path 282 can be followed again to access the current thermal image. The current thermal image can be acquired again at any appropriate time, such as after identifying and / or compensating for bubbles in the previous current thermal image. Therefore, when following the YES path 282, the current thermal image accessed in box 198 can again be understood as an iterative process of generating method 180.

[0070] However, if selected, then NO path 288 may be followed, such as that the procedure should be terminated. When the procedure is terminated, NO path 288 may be followed to end block 290. Ending method 180 may include completing the procedure on subject 28, such as removing instrument 24, or other appropriate steps. Further ending procedure 180 at block 290 may include terminating the application of energy for the selected procedure at a selected time, restarting the procedure, or other appropriate procedural steps.

[0071] As described above, method 180 may include various sub-steps or sub-routines that may be performed by a processor system including those discussed above and herein. Thus, in various embodiments, a bubble image library may be generated in block 188. Figure 4 And also refer to Figure 5 , describes the generation of generated bubble image library 188 in more detail. Generated bubble image library method 188 can be automatically performed using a processor system, such as processor system 40 and / or using input from user 25 and / or appropriate users. In general, the bubble image library is generated based on forming a plurality of bubble images based on a model, including changing the model based on the size and / or orientation of the bubbles in the image.

[0072] The bubble library method may be initiated in start block 300. Thereafter, a bubble model may be generated and / or accessed in block 304. The accessed bubble model may be based on selected information, such as a selected definition of a bubble. In various embodiments, the definition of a bubble may include or be defined by Equation 1:

[0073]

[0074] When a bubble is present in a substantially homogeneous structure, such as the brain 29, Equation 1 can be used to define the frequency shift of the bubble in Hertz. Equation 1 assumes or acknowledges that the bubble can be substantially gas or air, and that the difference in magnetic susceptibility between air or gas tissue can be about 9 ppm. Therefore, the magnetic susceptibility of the air in the bubble can be about 9 ppm less than the surrounding tissue, so d x = –9ppm. Under various assumptions, the gyromagnetic ratio is γ = 42.58 MHz / Tesla. B 0is the field strength of the imaging system 26, such as an MRI scanner, in Tesla. In addition, r is the radius of the bubble, and x, y, and z are in centimeters and indicate the bubble position, where z is B 0 direction. The frequency f is in Hertz. Typically, the bubble is assumed to be substantially spherical, so in the grid of x, y, and z coordinates, the values ​​within the bubble are defined or identified as zero and masked.

[0075] Thus, Equation 1 can be used to identify or calculate an image model at a three-dimensional grid (x, y, z) location within a slice. As described above, MRI can be used to generate image data, and the MRI image can have a selected slice width. Thus, the MRI slice image can have a three-dimensional volume, through which the dwell frequency shift Δf can be calculated using Equation 1. The total frequency shift at a selected location (x, y, z) during the excitation pulse is given by Equation 2:

[0076]

[0077] In Equation 2, γ is the same as above, G z is the frequency shift with slice gradient amplitude, z is the spatial position of the slice, and Δf 气泡 From Equation 1. Thus, given this frequency map and the frequency profile of the RF pulses in the MRI, interpolation can be used to calculate the slice profile for each spatial location of the bubble, which can be represented as (x, y, z). To determine the slice profile near the bubble, various assumptions can be made, such as a three millisecond per time bandwidth product of the RF pulses with a small excitation or deflection angle (e.g., about 10 degrees to about 40 degrees, including about 25 degrees) along with a three millimeter slice thickness.

[0078] Therefore, the bubble image can be depicted by Equation 3, which can also be called the slice profile of the bubble:

[0079] s TE (x,y,z)=x(x,y,z)e i2πTEΔf(x,y,z)

[0080] In Equation 3, the slice profile can be formed or advanced to the echo time represented by TE, so the spatial profile given by Equation 3 can be at the echo time of the imager. In Equation 3, the term s(x,y,z) is the signal at the end of the excitation pulse, and the index describes the time passed to the echo time. Therefore, TE is the time passed through the echo time of the signal or describes the time passed through the echo time of the signal so that the spatial profile is advanced to the echo time. The summation across the slice profile is then given by Δf(x,y,z), and this summation allows the slice profile of the bubble to be generated. Convolution averaging multiple x and y positions or direction rotations can be performed to account for signal loss at each x,y position.

[0081] Furthermore, it will be appreciated that the model of the bubbles may be based on taking into account contour effects within slices and / or without slices. However, as described above, the bubble image may be based on the accessed model.

[0082] As described above, the model accessed in box 304 can then be used to generate multiple bubble images in box 310. The multiple bubble images can be based on varying various characteristics of the bubble model. For example, variations in bubble radius can be used to identify or determine various sizes of bubbles. For example, the radius can be given in a selected dimension such as a voxel, and can range between about 1 voxel and about 50 voxels, including about 2 voxels and about 12 voxels, and further including a discrete number of voxels between 2 and 12. For example, the bubble library can contain 10 bubbles, each differing by 1 voxel, with the smallest bubble having a radius of 2 voxels and the largest bubble having a radius of 12 voxels. In addition, the bubble model can be relative to the axis of the imager: B 0 The axis is rotated or angled. Each of the bubbles of different radius can be rotated by a selected angle θ. The amount of rotation can be any suitable amount. For example, for a bubble library, each bubble can have an in-plane rotation of about -45 degrees to about +45 degrees in 15 degree steps. The amount of rotation at the x and z coordinates can be given by the x in Equation 4 and Equation 5, respectively. rot and Z rot gives:

[0083] X rot =x cos(θ)-Z sin(θ)

[0084] Z rot = x sin(θ)-Z cos(θ)

[0085] Therefore, each of the bubble images can contain 0 The axis has a bubble with a selected radius and / or a selected angle of rotation. Thus, as described above, each of the plurality of bubble images can be stored in a bubble image library that can be accessed in block 194. Thus, as described above, Figure 4 As shown in FIG. 1 , the plurality of images may be saved in block 314 in a bubble library that may be accessed in block 194 .

[0086] After the plurality of generated bubbles are saved in the library in box 314, it is determined in box 318 whether more bubbles are selected. If more bubbles are selected, a YES path 320 can be followed to box 310 to generate a plurality of bubble images that can be in addition to the previous plurality of bubble images. If it is determined in box 318 that no more bubbles are selected, a NO path 324 can be followed in box 330 to end. The bubble image library can be formed at any suitable time, such as before the start of surgery, during surgery, or at any selected time. In any case, the bubble image library can be generated as discussed above and can be used during the temperature sensing process.

[0087] Continue to refer Figure 5 And also refer to Figure 6 , a bubble library can be formed to contain bubble images that contain amplitude and phase differences. As will be appreciated by those skilled in the art, phase in MRI can be related to encoding due to optical resonance of the MRI imaging process. Typically, MRI imaging can include frequency encoding and phase encoding to determine information about each pixel or voxel in a slice image. Therefore, phase encoding can be used to help determine the temperature at a selected voxel within an image. Figure 6 As shown in FIG. 3 , the model accessed in block 304 can be used to generate a library image. Figure 6 In FIG. 3 , the library images of bubbles of a selected radius are plotted as magnitude images in the first row 340 and phase images in the second row 350. The bubble images in the bubble image library can also identify the level or amount of change. Figure 6 As shown in FIG. 1 , the amount or change of amplitude and phase variance can be included in the bubble images in the bubble image library and used to correlate with the comparison image, as discussed herein. The bubble library can further include relative to the axis B of the imaging system. 0 354 Rotated bubble model. Therefore, the library image can contain multiple images that are rotated in both amplitude and phase.

[0088] like Figure 6 In the figure, the first row 360 shows the axis B of the imager 0 In the second column 364, the magnitude image 340b and phase image 350b of the bubble are plotted. Finally, in the third column 368, the bubble is plotted at substantially 90 degrees or perpendicular to the axis B. 0 Depicted are a magnitude image 340c and a phase image 350c.

[0089] The bubble image library can contain more than Figure 6In any case, as further discussed herein, the bubble library can contain multiple images that allow for identification and analysis of thermal images. It should be understood that the recognition system can further interpolate between different bubble images to help identify bubbles in the current thermal image or the comparison image.

[0090] Continue to refer Figure 4 And also refer to Figure 7 , the thermal image that can be accessed in blocks 198 and 202 can be similar to Figure 3A and 3B Thus, the previous thermal image 150 and the current thermal image 160 are depicted. The current thermal image 160 may be called in block 198, and the previous thermal image 150 may be called or accessed in block 202, as shown. Figure 4 Shown in the middle.

[0091] As discussed above, the two images can be compared to each other in box 210. In order to compare the two images to each other, a ratio between the current thermal image 160 and the previous thermal image 150 can be obtained. That is, the current thermal image 160 can be divided by the previous thermal image 150. When the current thermal image 160 is divided by the previous thermal image 150, the ratio of each of the voxels or pixels within the current thermal image 160 can be determined. During the acquisition of image data of the subject 28, the subject 28 can remain substantially fixed relative to the imaging system 26. Therefore, time-varying images of the subject 28 can be acquired, which can be substantially registered and connected in series with each other. Therefore, the pixel or voxel position in the current thermal image 160 is known relative to the pixel or voxel at the same position in the previous thermal image. Therefore, the ratio between the two can be determined. It should be understood that other suitable differences or comparisons can be obtained, and the ratio is merely exemplary. However, the ratio of the current thermal image 160 to the previous thermal image 150 can produce the resulting image in column 380, such as Figure 7 Shown in the middle.

[0092] The resulting image or generated comparison image may include a generated amplitude comparison image 384 and a phase comparison image 388. The amplitude comparison image 384 may include a ratio of the density or intensity of each voxel between the current thermal image 160 and the previous thermal image 150. The pixel or voxel intensity may be displayed in the amplitude comparison image 384 for viewing by the user 25, such as on the display 22. However, it should be understood that the generated comparison image 380 may only be used for analysis by the workstation 42 to identify bubbles (if present) and compensate for them accordingly.

[0093] The generated comparison image 380 may also include a phase comparison image 388. As discussed above, the image data acquired using the MRI system 26 may acquire different types of data, including amplitude image data as depicted in the amplitude comparison image 384 and phase encoded image data as depicted in the comparison image 388.

[0094] like Figure 7 , there is a hole or dark area 166 in the image 160. The resulting comparative image may also include or identify an amplitude ratio, where the amplitude comparison image 384 includes a dark or low intensity area 392. The low intensity ratio area 392 illustrates that there is a small ratio between the current thermal image 160 and the previous thermal image 150. In various embodiments, as further discussed herein, an amplitude threshold may be used to help determine whether a data set, such as the comparative data set 380, contains bubbles. The amplitude threshold may be about 0.20 to about 0.90, and further includes about 0.50 to about 0.750, and further includes about 0.65. Thus, in various embodiments, a signal reduction of about 32% to about 40%, and further includes about 35%, may be used to help identify a relevant comparative data set for containing bubbles.

[0095] In addition, the phase comparison image 388 may also include a phase differential or comparison region 398. The phase comparison region 398 may also depict the phase change between the current thermal image 160 and the previous thermal image 150. Therefore, when bubbles appear in the subject 28, amplitude and phase differences may appear between the current thermal image 160 and the previous thermal image 150.

[0096] although Figure 7 Examples of amplitude comparison image 384 and phase comparison image 388 are depicted, but if bubbles are present in the comparison image data, the bubble image library accessed in block 194 may be compared to the comparison image data 380 to aid in determining and / or automatically identifying the bubbles. Figure 8 , the comparison image data 380 may include an amplitude comparison image 384 and a phase comparison image 388. The comparison image data 380 may be compared with the bubble library accessed in block 220, such as Figure 4 As shown in the figure. Figure 8 Schematically illustrated in FIG. 4 , a bubble image library 420 is illustrated. The bubble image library 420 may include a plurality of amplitude bubble models 424 or an array thereof and an array of phase bubble models 428 or a plurality of phase bubble models.

[0097] In the bubble image library 420, the array of amplitude bubble images 424 can contain a selected number of bubbles, such as a range between bubbles with a two-voxel radius in the first box 424a to bubbles with a twelve-voxel radius in the cell 424b. It should be understood that there can also be no bubble cells (e.g., no phase difference) 424c in the library 420.

[0098] Similarly, the phase bubble image library 420 may also include phase bubble images of multiple diameters, including two-voxel diameter cells 428a, twelve-voxel diameter cells 428b, and no-bubble cells 428c. As discussed above, the bubble image library 420 may also include phase bubble images with respect to the image axis B. 0 Multiple bubble images of rotating bubbles. Therefore, Figure 8 As exemplarily depicted in FIG. 4 , bubble image library 420 is merely an example of a plurality of bubble images that may be accessed in the bubble image library in block 194 .

[0099] Regardless of the number of bubble images accessible in the library 194 that can be compared, a selected number or a sub-number of bubble images from all bubble images from the bubble image library can be compared in block 220. Figure 8 As shown in FIG. 4 , each of the bubble images from library 420 may be compared to amplitude comparison image 384 , as shown by comparison lines 450 a and 450 b .

[0100] like Figure 8 , an amplitude image comparison may be performed on the amplitude comparison image 384, and the amplitude image comparison may allow for the generation of a correlation image data set or array 460. The correlation array 460 may include a representation of the correlation between each of the images in the bubble image library 420 and the comparison image data set 380. Thus, the correlation image array 460 may also include correlations with respect to phase bubble images, as illustrated by comparison lines 454a and 454b. The comparison lines illustrate the first and last bubble images compared to the comparison image data set 380. Thus, the correlation array 460 may include the same number of cells as the bubble image library, with each cell representing a comparison of a corresponding cell in the bubble image library. The first cell 460a includes the correlation of the first amplitude cell 424a with the comparison amplitude image 384 and the correlation of the first phase library cell 428a with the comparison phase image 388. The correlation array 460 includes cells that are correlated with each of the library images, such as including a maximum radius correlation cell 460b and a no bubble cell 460c. Thus, the correlation array 460 may contain the correlations between all bubble images and the comparison image data 380 .

[0101] Bubble image library 420 may contain bubble images of bubbles of selected size and / or orientation. In addition, the bubble images may be cropped to a selected size, such as one or two pixels larger than the bubble model. Thus, the dimensions of the bubble images may be smaller than the size of comparison image 380. Thus, to perform the comparison, bubble images from bubble image library 420 may be moved across comparison image 380 in a stepwise manner.

[0102] Correlation between a bubble image from bubble image library 420 and a portion of comparison image 380 will result in a high correlation, which can be depicted as bright pixels or voxels in the correlation image in correlation image array 460. Figure 8 As shown in FIG. 4 , in the corresponding bubble images of the bubble image library 420, each of the bubble images can have a selected geometry or intensity or phase deviation. When the bubble image from the bubble image library 420 is compared with a portion of the comparison image 380, each of the pixels or voxels can contain a selected correlation. The correlation can be low or high. A high or large correlation can be indicated as a high intensity or high correlation, which can be depicted in the correlation array 460. Likewise, it should be understood that the correlation data and the correlation array 460 can be depicted for use by the user 25 and / or in the system for identifying bubbles. However, a high correlation between the bubble image from the bubble image library 420 and the comparison image 380 can be identified.

[0103] In various embodiments, the bubble images in the bubble image library are masked to voxels with a phase shift greater than 0.1 radians. This masking helps locate correlations between the bubble image library images and the comparison images. Additionally, the cross-correlations can be normalized by the mean square amplitude of the bubble images from the bubble image library to allow for correlations between the comparison library entries. In various embodiments, particularly for complex-valued inputs of the comparison images, the correlations can be comparisons and can occur in the Fourier domain.

[0104] In various embodiments, the generation of bubble images in the bubble image library may contain non-square voxels, because the imaging resolution may be different at different sizes. Also, bubble rotation may be performed before or after synthesizing the bubble image, so the bubble coordinates may be rotated before calculating the image, or the image may be rotated afterwards.

[0105] The bubble image library can also be processed using techniques such as singular value decomposition or principal component analysis to reduce its size for more efficient computation. In other words, rather than directly calculating the correlation between the comparison image and each bubble image library entry, the correlation between the comparison image and a smaller number of optimized linear combinations of the bubble image library entries can be determined.

[0106] The correlation of each of the correlation images in the correlation array 460 may be given a correlation score S represented by Equation 6:ij .

[0107]

[0108] In Equation 6, for each of the bubble images from the bubble library, the correlation score may be the maximum value of the correlations between the bubble images having the selected radius i and angle j. As shown in Equation 6, the correlation score may attempt to provide a correlation To remove background noise, the correlation is the correlation between each of the bubble images in the bubble image library and the tissue mask. The tissue mask can be based on an initial image, such as an image and / or an initial thermal image before any resection or treatment is applied to the subject 28. Therefore, a mask can be used to remove erroneous correlations that may appear in the image. For example, in various embodiments, heat formation in the subject 28 may cause phase changes or phase shifts that may confuse bubble detection. Therefore, masking the image or removing the background can help achieve greater bubble detection accuracy. It should be understood that the optional tissue mask can also be formed with the thermal image from the immediately previous access from box 202. Therefore, the mask can contain image data or correlations based on possible heat that causes phase changes during treatment.

[0109] The bubble image library may have bubble images formed at a selected resolution, which may be significantly greater than the resolution of the comparison image. The resolution of the bubble images may be at a resolution large enough to allow detailed generation of the bubble images for comparison with the comparison image. Thus, during or after generation of the correlation image array 460, the correlation image array (the images contained therein) and / or the comparison image 380 (if scaled up) may be low pass filtered with a selected Gaussian function or kernel, such as a normalized Gaussian kernel. The resolution of the comparison image 380 and the correlation image 460 may be reduced to a resolution similar to that of the acquired image data, such as the current thermal image from block 194.

[0110] After low pass filtering, a pixel within the correlation image may be identified as a bubble pixel if the pixel or voxel has an amplitude below a selected amplitude (if selected). As discussed above, a ratio amplitude of 0.65 may be a selected threshold. Thus, if a voxel does not have at least a 35% signal reduction, it may not be included in a possible bubble detection. Additionally, if the signal in a voxel increases rather than decreases, it may not be included in a possible bubble determination. Furthermore, as discussed above, voxels having a selected correlation score of at least 0.2 may also not be included in a bubble detection. The correlation score may have any suitable value, such as 0.3, 0.4, or higher. A selected higher maximum value may reduce the number of voxels selected as being possibly within a bubble. Thus, voxels that meet at least these two requirements may be included in a bubble detection. Figure 8 As shown in FIG. 4 , the correlation image 460 can be used to identify one of the images or the correlation images as having a voxel or a group of voxels within a bubble, as shown at 490a and / or 490b. The image that may be contained within the bubble can then be confirmed or processed, as further discussed herein.

[0111] The comparison and determination of the related images or correlation 460 may be instructions executed, such as by the processor system 40. Thus, the correlation 460 may be determined substantially automatically based on instructions formed in accordance with the disclosed methods and processes.

[0112] Additionally, as discussed above, the bubble images from the bubble image library 420 may be compared to the comparison image 380. However, as discussed above, the determination of the bubbles may be related to being at or near the instrument 24 within the subject 28. Thus, the dimensionality of the comparison image 380 may be reduced, such as by identifying a region of interest (ROI) within the comparison image 380 and / or the thermal image. In various embodiments, as discussed above, the instrument 24 may be navigated by tracking using a selected tracking system.

[0113] Because the current thermal image accessed in block 198 may be generated with imaging system 26, the location of instrument 24 within the image data may be determined, as discussed above. Thus, comparison of bubble images from the bubble image library may be minimized to a selected region or volume around the distal end of instrument 24 within the subject (such as when the subject is registered to the image), such as comparison image 380. The amount of the image used for comparison with the bubble image bubble image may be selected to be only within a selected volume or region relative to the tracked location of the instrument.

[0114] In addition or as an alternative, the user 25 can also identify a region of interest for comparison with a bubble image from the bubble image library 420. The user 25 can identify the ROI through one or more input devices such as a keyboard 44. In various embodiments, the user 25 can draw or identify the ROI on the image 23 displayed by the display device 22. Therefore, in box 220, an optional area or volume of the region of interest can be identified for comparison. The comparison of the bubble image with the generated comparison image can be in one or both of the entire image and / or the selected region of interest. As described above, the region of interest can be based on the selection of the user 25, the tracked position of the instrument 24 such as tracked by the navigation system, or the inherent registration position of the image relative to the subject 28. For example, the ROI can be within a volume of about 0.1 cm to about 5 cm from the selected position of the end of the instrument 24. However, the bubble image can be compared with an appropriate portion of the comparison image to determine whether there are bubbles in the image.

[0115] Return to reference Figure 4After identifying the location of the bubble in the comparison image, it may be determined in block 248 whether to compensate. If it is determined not to compensate, various steps may be followed as discussed above, such as pausing treatment to allow the bubble to dissipate. However, if compensation is determined, a YES path 260 may be followed to remove the distortion / artifacts caused by the bubble from the current thermal image in block 270.

[0116] Compensation may include removing distortion, such as phase variance, caused by bubbles in the thermal image and / or the comparison image. Thus, in various embodiments, compensation may include subtracting a bubble image from a library of bubble images that best matches the identified bubble. Thus, bubble distortion is removed as the bubble image may be removed from the library of bubble images identified in the generated comparison image. The bubble image may be removed because it is placed on the thermal image or the comparison image as a determined center of the identified bubble in the image. In various embodiments, the center may be a weighted average center in the image. By removing information from the bubble image from the library of bubble images from the thermal image, the bubble may be subtracted or removed from the image.

[0117] In various embodiments, continue to refer to Figure 4 And also refer to Fig. 9 , alternatively and / or in greater detail, depicts the distortion removed in block 270. As described above, the removed distortion may be identified or determined as a subroutine as part of method 180. Also, as described above, the removal of distortion 270 and the temperature determination 274 may be instructions, such as executed using processor system 40. Thus, distortion cancellation and compensation may be determined substantially automatically based on instructions formed in accordance with the disclosed methods and processes.

[0118] Therefore, reference Fig. 9 , describing the dedistortion method or subroutine in more detail. Once the bubble is identified in box 244, all voxels in the comparison image that are part of the bubble and / or may be part of the bubble can be identified. Therefore, all voxels inside the bubble (i.e., as identified by the bubble image from the bubble image library accessed in box 194) can have a dipole field calculated for each voxel centered at each voxel. The dipole field can be generated as a matrix, which can be referred to as matrix A, and is defined by equation 7.

[0119]

[0120] Equation 7 is the squared difference of the x and y coordinates in the image divided by their sum. The coordinates are centered at the voxel location identified as xc and yc. Thus, calculation of the dipole field can be performed in block 480. The dipole field is a map based on the x and y locations within the image and can be formed as a vector in block 484. The vectors can form two columns of a matrix. The dipole matrix can then be used to analyze the comparison phase image 388, as described above in Figure 7 and Figure 8 discussed in .

[0121] In block 490, a dipole matrix may be fitted to a phase comparison phase image, such as image 388. The fitted phase image may be subtracted from the current thermal image in block 494. Subtraction of the comparison phase image 388 fitted with the dipole matrix may be used to determine appropriate thermal or phase changes due to thermal within the current thermal image that are not affected by the bubble.

[0122] The dipole matrix can be used to identify or clarify voxels in the current thermal image that have phase distortion caused by bubbles rather than phase changes caused by heating of tissue within the subject 28. Thus, subtracting the comparison phase image fitted with the dipole matrix from the current thermal image eliminates phase distortion caused by bubbles rather than heat. Thus, removing the distortion / artifact of bubbles in block 270 can allow the temperature at all voxels within the current thermal image 198 to be determined in block 274.

[0123] Continue to refer Fig. 9 and return the reference Figure 4 , the determination of the temperature in the current thermal image can be based on the removal of the phase distortion caused by the bubbles. Therefore, once the bubble phase is removed, the temperature can be determined in block 274. In addition, referring to Fig. 9 , the temperature determination may include various sub-steps or sub-routines. For example, the temperature determination in block 274 may include temperature unwrapping in block 510. The temperature unwrapping in block 510 may include correcting for phase wrapping when phase encoding the thermal determination image accessed in block 198. Therefore, in block 510, temperature unwrapping may result due to the phase.

[0124] Temperature determination may also include drift removal in box 520. Drift removal may include determining a temperature drift that varies over time. Drifting temperatures that vary over time may occur for a variety of reasons, and drift removal may include determining a temperature drift that varies over time, such that the accumulation of phase drift is monitored and the temperature data is adjusted across the image anatomy for the drift artifact. Thus, all thermal images may be summed to determine masking and / or subtraction of thermal drift that may have occurred prior to the current thermal image accessed in box 194. Other appropriate methods may also be used to determine drift and / or drift removal. For example, a drift correction may be derived from a transient heating image (e.g., a current thermal image) by fitting a low-order polynomial to the entire phase difference image (e.g., the phase portion of the comparison image (i.e., the phase variance image 388) and then subtracting it from a temperature map based on the current thermal image.

[0125] Finally, a temperature map may be produced in box 530 based on the removal of bubble phase distortion and taking into account optional additional features, such as temperature deconvolution and drift removal in boxes 510, 520, respectively, as discussed above. The temperature map may include a temperature determined for each voxel in the current thermal image accessed in box 198. The temperature determination may also include or be a temperature difference from a previous thermal image. In addition, as described above, the determination may be based on information collected using image data acquired by the imaging system 26 of the subject 28. In various embodiments, the information may include phase changes or other information, such as relaxation times, for each voxel in the image. In various embodiments, the temperature map may be determined according to generally known techniques, such as those sold by Medtronic. The temperature determination is performed using those techniques used in cooling laser fiber systems. However, the temperature map generated in block 530 may be derived after removing bubbles or potential bubbles identified in the current thermal image according to method 180 including the various sub-steps described above.

[0126] Thus, as discussed above, the procedure may be performed on a subject and the temperature may be determined using the image. Incorporating or based on the method described above, the temperature may be determined regardless of whether bubble formation occurs. Thus, bubbles may appear in the image, which may be automatically identified based on the algorithm described above according to instructions executed by the processor, and a corrected or undistorted temperature map may be generated based on the current thermal image. Thus, the user 25 may determine or have determined a temperature map of the subject.

[0127] Return to reference Figure 1 and 2 And further reference Figure 4, in box 220, at least one bubble image from the accessed bubble image library can be compared with the comparison image. When comparing at least one bubble image library, as described above, all images in the image bubble library can be compared with the comparison bubble image. As described above, each of the bubble images can contain selected pixels or voxels (based on the type of image and comparison image generated) to allow comparison between the bubble image and the comparison image. Typically, a pair-by-pair comparison between pixels and / or voxels in the bubble image is performed with pixels and / or voxels in the comparison image. However, comparing the bubble image with the entire thermal image may contain irrelevant or redundant correlations and / or may increase analysis time. Therefore, in various embodiments, as described above, a region of interest (ROI) can be determined to limit or restrict only the area or volume in which the bubble image is compared with the comparison image. In various embodiments, the ROI can be determined based on navigating the instrument 24 in the subject 28.

[0128] Additional references Fig.10 , depicting a navigation-determined region of interest 600. The navigation-determined region of interest may be incorporated into the image, such as immediately before comparing at least one bubble image from the accessed bubble image library with the current image in block 220. Figure 4 In the method 180 shown in FIG. 1 , it should also be understood that Figure 4 , the determination of the ROI may be a subroutine incorporated into the comparison in block 220. Thus, the determined ROI 600 may be understood as a subroutine incorporated into the method 180. Thus, as described above, the method 600 may be instructions such as executed by the processor system 40. Thus, the method 600 may be substantially automatically determined based on instructions formed in accordance with the disclosed methods and processes.

[0129] Typically, when navigating the instrument 24 during a selected procedure, the instrument 24 may be tracked with a selected tracking system, such as the tracking system 50 discussed above, to determine the position of at least a portion of the instrument 24. Thus, the determined ROI method 600 may begin in the method 180 at the comparison block 210 and continue tracking the instrument in block 614.

[0130] When the instrument is tracked in box 614, the position of the instrument 24 can be determined by the navigation system 20. The position of the instrument 24 relative to the subject 28 can be determined, such as using the DRF58. As described above, the image of the subject 28, including the image 23, can be registered to the patient 28. In various embodiments, the image 23 can be registered to the subject 28 in box 618. Therefore, in box 614, based on the tracking instrument, the tracked position of the instrument 24 relative to the image 23 can be known. The registration can occur in any suitable manner, including the manner discussed above, such as identifying reference points in the subject 28 and the image 23 (the reference points can be natural or artificially implanted). In any case, the images can be registered in box 618.

[0131] Thus, the tracked position of the instrument in block 614 may be determined relative to the image in block 622. When determining the position of the instrument in block 622, an area within the image 23 may be identified in image space. As described above, the position of at least a portion of the instrument, such as the terminal end 110 of the instrument 24 and / or the distal end 104 of the energy delivery device 100, may be determined. The position of a portion of the instrument, such as a fiber optic element or the terminal end of the energy delivery device 100, may be used to identify an area relevant to temperature determination.

[0132] By determining the region of interest in box 628, the determined region of interest can be based on the instrument position determined in box 622. The determined region of interest can contain a selected area or volume around or near the determined position of the instrument or a portion of the instrument. For example, the determined region of interest can be defined as a volume having a radius of a selected length (e.g., about 1 cm to about 6 cm and / or about 2 pixels or voxels to about 12 pixels or voxels). The region of interest can be located at or near the center of the determined position of the portion of the instrument and can be determined in box 628.

[0133] In various embodiments, a processor, such as processor system 40 discussed above, may call for a predetermined size of the region of interest or determine the size of the region of interest. However, it should be understood that user 25 may also define the region of interest relative to the tracked position of the instrument and the determined position of the instrument in block 622. Thus, determining the region of interest in block 628 may identify a portion of image 23 (e.g., the tracked center of the heated portion of the instrument and a volume within a selected radius from the center).

[0134] As described above, the determination of the ROI may be a subroutine of block 220. However, if Fig.10, the determination of ROI 600 may be inserted between generating the comparison image in block 210 and comparing at least one bubble image from the accessed bubble image library with the current comparison image in block 220. Thus, the determination of the ROI by navigation of the instrument 24 may be understood to be inclusive or included as a selected option within the method 180.

[0135] Return to reference Figure 4 As discussed above, at block 220, a comparison is made in method 180 to determine whether bubbles exist or may exist in the image for a portion of the image. As discussed above, reference Figure 4 and Figure 5 , a bubble image may be generated and / or accessed for comparison with a comparison image. The bubble image may be based on a model of bubbles and an image of the model bubbles, including amplitude and phase variances. However, in various embodiments, in addition to and / or as an alternative to the bubble image model, bubbles may be identified and / or possible bubbles may be identified by directly analyzing the comparison image. In various embodiments, in addition to and / or as an alternative to the bubble image model as discussed above, a heuristic approach may be applied.

[0136] Continue to refer Figure 4 And also refer to Fig.11 , method 220b is depicted. As discussed above, method 220b may be a supplement and / or alternative to the comparison of bubble images from a bubble image library. However, comparison method 220b may be included in method 180, such as Figure 4 20b to determine whether bubbles are present in block 230 and to determine the identified location of the bubbles in the comparison image in block 244. Thus, as discussed above, the comparison method 220b may be included or understood as a subroutine within the method 180.

[0137] Therefore, as discussed above and in articles such as Figure 6 and Figure 8 The bubble image comparison algorithms or systems depicted in the various figures of can also be alternatives and / or supplements to method 220b. Figure 6 and Figure 8 The method including the bubble image library shown in can also be understood as a subroutine of method 180 .

[0138] As discussed above, the heuristic or non-model comparison 220b may begin at block 210. A comparison image may be generated at block 210 and received for comparison at block 660. The received one or more comparison images may include comparison image data 668, such as Fig.12. As discussed above, the comparative image data 668 can be similar to the image data 380. Typically, the comparative image data can be a ratio of the current thermal image 160 to a prior (prior / previous) thermal image 150. As discussed above, the current thermal image 160 may or may not include one or more voxels or pixels that include a selected change or have a selected change when compared to the prior thermal image 150. In various embodiments, as discussed above, the comparative image data 668 can be based on a ratio of the current thermal image 160 to the prior thermal image 150. Also as discussed above, the comparative image data 668 can include amplitude image data 670 and phase variance image data 674. As Fig.12 As exemplarily shown in FIG. 6 , the amplitude image data 670 may include an amplitude variation or decrease region 678 , and the initiated phase variance 674 may include a phase variance region (region / area) 682 .

[0139] In the comparison method 220b, the filter 692 may be moved over the comparison image in block 688. The filter may be defined and / or saved in a selected memory, such as in the memory 46. The processor system 40 may then call the filter and compare it to the comparison image data or move it over the comparison image data 668, as discussed further herein.

[0140] The filter may be defined to attempt to identify or identify clusters or local regions of voxels or pixels that contain a selected criterion or variance. The variance may be predefined and contained within the filter stored in memory 46. However, in various embodiments, the user 25 may also identify selected features or criteria to be contained in the filter for comparison with the comparison image in block 688.

[0141] The filter can include a selected size, such as about 2 voxels to about 15 voxels, including about 7 voxels to about 11 voxels, and further including about 9 voxels. Thus, the filter can have a selected size and can be moved within the selected size of the comparison image. As discussed above, the filter can be moved within the entire image. However, in various embodiments, the filter can also be moved within the region of interest. As described above, the region of interest can include a manually selected region of interest (e.g., a region of interest identified by user 25, such as by drawing an ROI in image 23 with input) and / or based on, for example, Fig.10 600. Thus, it should be appreciated that the filter may be applied to the comparison image in any suitable region, including the entire image or only a region of interest which may be smaller than the entire image.

[0142] The filter may determine or identify selected voxels within the comparison image 668 that may contain bubbles or be determined to be within bubbles. Thus, the filter may be applied to the comparison image data 668 by the processor system 40 in a manner similar to the application of the bubble image as discussed above. Thus, the filter may be applied in a substantially pair-wise manner relative to the comparison image 668 to determine whether the voxels meet the comparison and / or determination of selected thresholds, as further discussed herein.

[0143] like Fig.12 The filter 692 illustrated in FIG. 6 may be illustrated as a regional or volume filter 692 as discussed above. In various embodiments, the filter may include / inclusive of at least two features or criteria, but the at least two features or criteria may be Fig.12 670. For example, in the magnitude image 670, the filter 692 may include a selected size, as discussed above, and identify or compare the magnitude image 670 to determine a selected signal drop. The selected signal drop may include or be defined as a ratio of voxels or a magnitude variation of the comparison image data 668 that is at least about 0.5 to about 0.95 and further includes about 0.7 to about 0.9, and further includes an amplitude variance of about 0.8 in the comparison image 668. In other words, the filter may identify a signal drop of about 20% from the thermal image to the current thermal image as being slightly contained within a bubble.

[0144] The filter 692b may include a second standard that is compared to or moved over the phase variance image 674. The filter may identify voxels in the phase variance image 674 that have a phase variance of about 0.5 radians to about 1.5 radians, further including about 1 radian. The phase variance may be identified or determined on a per-voxel basis, such as in a pair-wise comparison between the voxels in the filter 692b and the phase variance image 674.

[0145] Thus, as discussed above, the filter 692 is moved over or compared to the comparison image data 668, which includes the entire image and / or within the region of interest. Based on the evaluation of the voxels within the filter, it is determined in box 698 whether the identified voxel is likely to be within a bubble. As discussed above, the filter can be used to identify voxels that are likely to be within a bubble based on the selected criteria and / or thresholds regarding amplitude and phase variance described above. Then, in box 698, all voxels identified as being likely to be within a bubble based on the filter 692 can be determined or saved. Generally, if a voxel meets two criteria such as having an amplitude variance of approximately 0.8 (i.e., a signal reduction of approximately 20%) and a phase variance of approximately 1 radian, it can be determined that the voxel is likely to be within a bubble.

[0146] Once a voxel is determined or identified as being potentially within a bubble in block 698, the size of the voxels within a selected distance of each other may be derived in block 702. As discussed above, filter 692 may be used to determine whether a selected voxel or voxels have a selected amplitude variation (e.g., signal drop) and / or phase variance. Typically, as discussed above, a voxel determined to be potentially within a bubble will be required to contain two thresholds.

[0147] The bubbles may be determined to have a selected size and / or geometry. For example, it may be assumed that the bubbles have a radius of at least about 2 voxels and / or equal to or less than about 12 voxels. Thus, determining the size of a voxel cluster in box 702 may be used to identify whether bubbles are present in the comparison image 668. Clusters may be voxels that are adjacent to each other (e.g., touching) or within a selected distance (e.g., 0.5 voxels apart) that meet the bubble filtering criteria. All voxels that meet the distance criteria may be identified as clusters. Once the size of any voxel cluster is determined in box 702, it may be determined in box 230 whether bubbles are present.

[0148] Determining whether bubbles are present in the comparison image based on the heuristic comparison 220b in block 230 may include determining whether any voxels determined in block 698 meet the size identified or selected in block 230 once the cluster has been determined in block 702. Thus, if a voxel cluster has been identified and contains the size of at least 2 voxels, then it may be determined in block 230 that bubbles are present in the comparison image. Thus, the YES path 238 may be followed, as described above. Figure 4 As shown and discussed in.

[0149] If it is determined that there are no clusters or no voxel clusters meet the size criteria, such as less than 2 voxels and / or greater than 12 voxels, then it can be determined in determination box 230 that bubbles are not present in the image and the NO path 234 can be followed. It should be understood that the cluster size can be predetermined and included in the filter for analysis by the processor system 40. It should also be understood that the user 25 can also input a selected cluster size for analysis of the comparison image 668. Therefore, the comparison method 220b can be used to compare and / or help identify or determine whether bubbles are present in the comparison image. As discussed above, the comparison is performed with the bubble image library image individually and / or in combination.

[0150] Example embodiments are provided so that the present disclosure is comprehensive and the scope is fully conveyed to those skilled in the art. Many specific details are set forth, such as examples of specific components, devices, and methods, to provide a thorough understanding of the embodiments of the present disclosure. Those skilled in the art will appreciate that specific details need not be employed, that example embodiments may be implemented in many different forms, and should not be construed to limit the scope of the present disclosure. In some example embodiments, well-known methods, well-known device structures, and well-known technologies are not described in detail.

[0151] Instructions may be executed by a processor and may include software, firmware, and / or microcode and may refer to programs, routines, functions, classes, data structures, and / or objects. The term shared processor circuit encompasses a single processor circuit that executes some or all code from multiple modules. The term grouped processor circuit encompasses a processor circuit that combines with another processor circuit to execute some or all code from one or more modules. References to multiple processor circuits encompass multiple processor circuits on discrete dies, multiple processor circuits on a single die, multiple cores of a single processor unit, multiple threads of a single processor circuit, or a combination of the above. The term shared memory circuit encompasses a single memory circuit that stores some or all code from multiple modules. The term grouped memory circuit encompasses a memory circuit that combines with another memory to store some or all code from one or more modules.

[0152] The apparatus and methods described in this application may be implemented in part or in whole by a special-purpose computer created by configuring a general-purpose computer to perform one or more specific functions implemented in a computer program. The computer program includes processor-executable instructions stored on at least one non-transitory, tangible computer-readable medium. The computer program may also include or rely on stored data. The computer program may include a basic input / output system (BIOS) that interacts with the hardware of the special-purpose computer, device drivers that interact with specific devices of the special-purpose computer, one or more operating systems, user applications, background services, background applications, etc.

[0153] A computer program may include: (i) assembly code; (ii) object code generated by a compiler from source code; (iii) source code executed by an interpreter; (iv) source code compiled and executed by a just-in-time compiler, (v) descriptive text for parsing, such as HTML (Hypertext Markup Language) or XML (Extensible Markup Language). By way of example only, source code may be C, C++, C#, Objective-C, Haskell, Go, SQL, Lisp, ASP, Perl, HTML5, Ada, ASP (Active Server Pages), Perl, Scala, Erlang, Ruby, Visual Lua or To write.

[0154] Communications may include wireless communications described in the present disclosure, which may be conducted in whole or in part in accordance with IEEE Standard 802.11-2012, IEEE Standard 802.16-2009, and / or IEEE Standard 802.20-2008. In various embodiments, IEEE 802.11-2012 may be supplemented by Draft IEEE Standard 802.11ac, Draft IEEE Standard 802.11ad, and / or Draft IEEE Standard 802.11ah.

[0155] Processor or module or 'controller' may be replaced by the term 'circuitry'. The term 'module' may refer to or be part of or include: an application specific integrated circuit (ASIC); a digital, analog or hybrid analog / digital discrete circuit; a digital, analog or hybrid analog / digital integrated circuit; a combinational logic circuit; a field programmable gate array (FPGA); a processor circuit (shared, dedicated or grouped) that executes code; a memory circuit (shared, dedicated or grouped) that stores code executed by the processor circuit; other suitable hardware components that provide the functionality; or a combination of some or all of the above, such as in a system on a chip.

[0156] The foregoing description of the embodiments is provided for the purpose of illustration and description. It is not intended to be exhaustive or to limit the present disclosure. The individual elements or features of a specific embodiment are generally not limited to the specific embodiment, but are interchangeable when applicable and can be used in the selected embodiment (even if not specifically shown or described). The individual elements or features of a specific embodiment can also change in many ways. Such changes should not be considered as departing from the present disclosure, and all such modifications are intended to be included in the scope of the present disclosure.

[0157] Further areas of applicability of the present teachings will become apparent from the detailed description provided above.It should be understood that the detailed description and specific examples, while indicating various embodiments, are intended for purposes of illustration only and are not intended to limit the scope of the present teachings.

Claims

1. A method for determining the presence of bubbles in an image, comprising: accessing a comparison image generated by comparing the first image and the second image; comparing at least a first filtering criterion and a second filtering criterion to the comparison image; Determining whether one or more voxels in the comparison image satisfy both the first filtering criterion and the second filtering criterion ； as well as determining a size of an object including one or more voxels that are within a selected distance of each other and that are determined to satisfy both the first filtering criterion and the second filtering criterion; as well as identifying a bubble in at least one of the first image or the second image when the determined size is within a selected size, Therein, at least the first filtering criterion is operable to identify a phase change between the first image and the second image.

2. The method according to claim 1, in, The first image precedes the second image. 3 . The method of claim 1 , wherein the first filtering criterion comprises an amplitude difference between the first image and the second image in the comparison image. The method of claim 1 , wherein the second filtering criterion comprises a phase variance between the first image and the second image in the comparison image.

5. The method according to claim 1 , wherein at least one filtering criterion is compared with the current image. include: selecting a first area within the second image; determining whether a first voxel in the second image satisfies the criterion; selecting a second area within the second image; as well as A determination is made as to whether a second voxel in the second image satisfies the criterion.

6. The method according to claim 5, further comprising: include: selecting a region of interest within the second image; as well as Only the first region and the second region within the region of interest are selected. The method of claim 6 , wherein selecting the region of interest within the second image comprises determining a position of an instrument.

8. The method of claim 1, wherein the first filtering criterion comprises determining whether at least one voxel in the comparison image contains a magnitude ratio of 0.

8.

9. The method of claim 1, wherein the second filtering criterion comprises determining whether at least one voxel in the second image contains a phase variance of one radian.

10. The method of any one of claims 1 to 4, wherein determining the size of all output voxels within the selected distance of each other comprises determining the size of all of the output voxels that are adjacent to another output voxel.

11. The method according to claim 10, further comprising: include: When the determined size has a diameter of at least two voxels, a bubble is identified in the second image.

12. The method according to any one of claims 1 to 4, further comprising: include: A temperature map is determined based on the second image after removing distortions caused by identified air bubbles.

13. The method of claim 1, wherein the selected size is between two voxels and twelve voxels.

14. The method according to claim 13, wherein the first filtering criterion comprises an amplitude ratio of 0.8, and the second filtering criterion comprises a phase variance of one radian.

15. A system for determining the presence of bubbles in an image, which comprises: an input system for inputting a comparison image; a memory system on which a filter having at least a first filtering criterion and a second filtering criterion is stored; and a processor system operable to execute instructions to: invoke from the memory system the filter having at least the first filtering criterion and the second filtering criterion, determine that one or more voxels in the comparison image satisfy both the first filtering criterion and the second filtering criterion, and determine the size of an object of one or more voxels in the comparison image that are included within a selected distance of each other and are determined to satisfy the first filtering criterion and the second filtering criterion, wherein the first filtering criterion comprises an amplitude difference in the comparison image, and the second filtering criterion comprises a phase difference in the comparison image.

16. The system according to claim 15, wherein the processor system is operable to execute further instructions to generate the comparison image as a ratio of a first image to a second image.

17. The system according to claim 16, wherein the processor system is operable to execute further instructions to identify a bubble in at least one of the first image or the second image when the determined size is a selected size.

18. The system according to any one of claims 15 to 17, wherein the first filtering criterion comprises an amplitude ratio of 0.8, and the second filtering criterion comprises a phase variance of one radian.

Images