CN110827401A - Scanning imaging system for interventional therapy - Google Patents
Scanning imaging system for interventional therapy Download PDFInfo
- Publication number
- CN110827401A CN110827401A CN201911120194.8A CN201911120194A CN110827401A CN 110827401 A CN110827401 A CN 110827401A CN 201911120194 A CN201911120194 A CN 201911120194A CN 110827401 A CN110827401 A CN 110827401A
- Authority
- CN
- China
- Prior art keywords
- image
- data
- imaging
- interventional
- interventional therapy
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000003384 imaging method Methods 0.000 title claims abstract description 68
- 238000002560 therapeutic procedure Methods 0.000 title claims abstract description 55
- 238000007781 pre-processing Methods 0.000 claims abstract description 21
- 238000000034 method Methods 0.000 claims abstract description 19
- 230000000694 effects Effects 0.000 claims abstract description 12
- 238000012545 processing Methods 0.000 claims abstract description 12
- 230000008569 process Effects 0.000 claims abstract description 6
- 230000002452 interceptive effect Effects 0.000 claims description 19
- 230000005284 excitation Effects 0.000 claims description 14
- 230000011218 segmentation Effects 0.000 claims description 12
- 230000003287 optical effect Effects 0.000 claims description 10
- 230000005540 biological transmission Effects 0.000 claims description 8
- 230000004069 differentiation Effects 0.000 claims description 6
- 230000002708 enhancing effect Effects 0.000 claims description 5
- 238000001914 filtration Methods 0.000 claims description 5
- 230000003993 interaction Effects 0.000 claims description 5
- 210000000056 organ Anatomy 0.000 claims description 4
- 238000012546 transfer Methods 0.000 claims description 4
- 238000006243 chemical reaction Methods 0.000 claims description 3
- 238000002059 diagnostic imaging Methods 0.000 claims description 3
- 238000013519 translation Methods 0.000 claims description 3
- 238000005481 NMR spectroscopy Methods 0.000 claims description 2
- 230000003321 amplification Effects 0.000 claims description 2
- 230000008859 change Effects 0.000 claims description 2
- 238000002591 computed tomography Methods 0.000 claims description 2
- 238000010276 construction Methods 0.000 claims description 2
- 238000009795 derivation Methods 0.000 claims description 2
- 238000001514 detection method Methods 0.000 claims description 2
- 230000008030 elimination Effects 0.000 claims description 2
- 238000003379 elimination reaction Methods 0.000 claims description 2
- 238000005286 illumination Methods 0.000 claims description 2
- 230000000977 initiatory effect Effects 0.000 claims description 2
- 238000013507 mapping Methods 0.000 claims description 2
- 239000002184 metal Substances 0.000 claims description 2
- 238000003199 nucleic acid amplification method Methods 0.000 claims description 2
- 238000005070 sampling Methods 0.000 claims description 2
- 239000000126 substance Substances 0.000 claims description 2
- 230000001131 transforming effect Effects 0.000 claims description 2
- 238000004458 analytical method Methods 0.000 abstract description 2
- 238000000968 medical method and process Methods 0.000 abstract description 2
- 238000002604 ultrasonography Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 238000003709 image segmentation Methods 0.000 description 2
- 125000006850 spacer group Chemical group 0.000 description 2
- 238000001228 spectrum Methods 0.000 description 2
- 238000003745 diagnosis Methods 0.000 description 1
- 201000010099 disease Diseases 0.000 description 1
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000001575 pathological effect Effects 0.000 description 1
- 238000001834 photoacoustic spectrum Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 230000003595 spectral effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000001356 surgical procedure Methods 0.000 description 1
- 230000001225 therapeutic effect Effects 0.000 description 1
- 238000012285 ultrasound imaging Methods 0.000 description 1
- 238000012800 visualization Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T19/00—Manipulating 3D models or images for computer graphics
- G06T19/20—Editing of 3D images, e.g. changing shapes or colours, aligning objects or positioning parts
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/11—Region-based segmentation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/155—Segmentation; Edge detection involving morphological operators
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H30/00—ICT specially adapted for the handling or processing of medical images
- G16H30/20—ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H30/00—ICT specially adapted for the handling or processing of medical images
- G16H30/40—ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2200/00—Indexing scheme for image data processing or generation, in general
- G06T2200/08—Indexing scheme for image data processing or generation, in general involving all processing steps from image acquisition to 3D model generation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10132—Ultrasound image
- G06T2207/10136—3D ultrasound image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2219/00—Indexing scheme for manipulating 3D models or images for computer graphics
- G06T2219/20—Indexing scheme for editing of 3D models
- G06T2219/2016—Rotation, translation, scaling
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Theoretical Computer Science (AREA)
- Radiology & Medical Imaging (AREA)
- General Health & Medical Sciences (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Public Health (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Computer Graphics (AREA)
- Epidemiology (AREA)
- Software Systems (AREA)
- Medical Informatics (AREA)
- Primary Health Care (AREA)
- Geometry (AREA)
- Architecture (AREA)
- Computer Hardware Design (AREA)
- General Engineering & Computer Science (AREA)
- Ultra Sonic Daignosis Equipment (AREA)
Abstract
The scanning imaging system for interventional therapy is responsible for reading in interventional therapy image data through the interventional therapy data reading module, the image preprocessing module preprocesses each slice of the medical data according to the operation of a user after the medical data transmitted by the interventional therapy data reading module is obtained, the specific tissue is segmented through the algorithms of body imaging, surface imaging and the like, the imaging of the specific tissue is realized, and finally the system displays the operation effect through the modules and can switch among different views. The invention effectively ensures the effective acquisition and format unification processing of the equipment images in the interventional medical process, avoids the format incompatibility of different medical images, effectively processes and stores the interventional images, ensures the imaging effect of related scanned images and improves the query analysis efficiency.
Description
Technical Field
The present application relates to the field of medical image segmentation technologies, and in particular, to a method and an apparatus for segmenting a three-dimensional medical image.
Background
Medical image segmentation is the basis of subsequent processing of three-dimensional visualization, surgical simulation, graph-guided surgery and the like of normal tissues and pathological tissues, and the accuracy of segmentation is very important for doctors to judge the real condition of patient diseases and make corresponding diagnosis plans.
The video frame rate output by many ultrasound imaging systems is fixed. For example, the image is output at 30Hz or 60Hz to simplify conversion to the NTSC standard video signal required by the video cassette recorder. Matching the video frame rate to the frame rate used in typical applications simplifies the recording of ultrasound scans. Existing (Off-the-shelf) parts may also be used to generate video in an ultrasound system.
Since the current medical imaging device usually has only one fixed scanning direction during scanning, in the prior art, the starting position of the supplementary scanning is usually the ending position of the first scanning, and this kind of supplementary scanning method can only correct the situation that the deviation area is located behind the scanning area of the first scanning. However, since the deviation region may also occur before the start position of the first scan (e.g., a missing scan region) or in the scan region of the first scan (e.g., a motion artifact region), a more flexible compensation scan method is required. In the process of obtaining the locating piece, an operator is often required to manually position according to the scanned part of the human body, and the locating piece has higher technical requirements on the operator. Therefore, an efficient and reliable method for setting the scanning of the spacer is needed to improve the working efficiency of obtaining the spacer.
Disclosure of Invention
In order to solve the problems of difficult image collection and poor imaging effect in the interventional therapy in the current medical scanning imaging process, the invention provides a scanning imaging system for interventional therapy, which is characterized by comprising the following components:
the interventional therapy data reading module is responsible for reading in interventional therapy image data, supports image files in JPG and IMG formats besides files in DICOM format, unifies the image files into intermediate data in the same format, excites to obtain interventional therapy signals, and delivers the interventional therapy signals to the image preprocessing module for processing;
the image preprocessing module is used for preprocessing each slice of the medical data according to the operation of a user after the medical data transmitted by the interventional therapy data reading module is obtained, and the preprocessing comprises filtering, enhancing, registering, cutting a three-dimensional ultrasonic image, denoising and binaryzation;
the three-dimensional imaging module is used for imaging the preprocessed medical slice into a three-dimensional stereo model, and realizing the segmentation of a specific tissue by adopting a segmentation method combining binaryzation and morphology through algorithms such as volume imaging or surface imaging and the like according to the requirements of doctors so as to realize the imaging of the specific tissue;
the system comprises an interventional interactive module, a system and a display module, wherein the interventional interactive module adopts interactive volume data imaging, a user performs rotation, zooming and translation operations on an imaged three-dimensional model, and the system displays the operation effect through the modules and can switch among different views.
The scanning imaging system for interventional therapy is responsible for reading in interventional therapy image data through the interventional therapy data reading module, the image preprocessing module preprocesses each slice of the medical data according to the operation of a user after the medical data transmitted by the interventional therapy data reading module is obtained, and realizes the segmentation of specific tissues through algorithms such as body imaging or surface imaging and the like so as to realize the imaging of the specific tissues; and finally, the system displays the effect of the operation through the modules and can switch between different views. The invention effectively ensures the effective acquisition and format unification processing of the equipment images in the interventional medical process, avoids the format incompatibility of different medical images, effectively processes and stores the interventional images, ensures the imaging effect of related scanned images and improves the query analysis efficiency.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a block diagram of an interventional scanning imaging system according to the present invention.
Fig. 2 is a flowchart of the operation of the modules of the scanning imaging system for interventional therapy according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the present invention claims a modular block diagram of an interventional therapeutic scanning imaging system.
The invention relates to an interventional therapy scanning imaging system, which is characterized by comprising the following modules according to the working flow chart of the interventional therapy scanning imaging system with reference to the attached figure 2:
the interventional therapy data reading module is responsible for reading in interventional therapy image data, supports image files in JPG and IMG formats besides files in DICOM format, unifies the image files into intermediate data in the same format, excites to obtain interventional therapy signals, and delivers the interventional therapy signals to the image preprocessing module for processing;
the image preprocessing module is used for preprocessing each slice of the medical data according to the operation of a user after the medical data transmitted by the interventional therapy data reading module is obtained, and the preprocessing comprises filtering, enhancing, registering, cutting a three-dimensional ultrasonic image, denoising and binaryzation;
the three-dimensional imaging module is used for imaging the preprocessed medical slice into a three-dimensional stereo model, and realizing the segmentation of a specific tissue by adopting a segmentation method combining binaryzation and morphology through algorithms such as volume imaging or surface imaging and the like according to the requirements of doctors so as to realize the imaging of the specific tissue;
the system comprises an interventional interactive module, a system and a display module, wherein the interventional interactive module adopts interactive volume data imaging, a user performs rotation, zooming and translation operations on an imaged three-dimensional model, and the system displays the operation effect through the modules and can switch among different views.
Furthermore, the interventional therapy data reading module is responsible for reading in interventional therapy image data, supports image files in the JPG and IMG formats in addition to files in the DICOM format, unifies the image files into intermediate data in the same format, excites and obtains interventional therapy signals, and delivers the interventional therapy signals to the image preprocessing module for processing, and the interventional therapy data reading module comprises:
the digital image of the biological tissue and organ is obtained by scanning the interventional therapy image data through medical imaging equipment;
interpolating between adjacent layers, representing the scanned interventional therapy image data as a sum of image information based on the interventional therapy image data in the sample library and interventional differentiation image information;
the data field is formed by the superposition of MRI and CT tomograms generated by a computer tomography scanner and nuclear magnetic resonance in one spatial direction;
obtaining interventional differentiation image information by utilizing parallel imaging, and forming sparse representation of scanned interventional treatment image data through a multi-coil model coefficient of the interventional image body and a coefficient of the interventional differentiation image information in a sparse transform domain; the data field data is abstracted into a three-dimensional array obtained by uniformly sampling objects defined in a three-dimensional closed space, including organism tissues and organs;
constructing an interventional image volume according to the reference prior information, and capturing image information based on interventional treatment image data in a sample library through the interventional image volume;
interventional therapy image data jointly utilizing an interventional image volume, parallel imaging and an objective function enhanced sparse imaging scan.
Further, after obtaining the medical data transmitted by the interventional therapy data reading module, the image preprocessing module preprocesses each slice of the medical data according to the operation of the user, where the preprocessing includes filtering, enhancing, registering, three-dimensional ultrasound image clipping, denoising, and binarization, and specifically includes:
adopting a sliding window containing odd points, and replacing the gray value of the central point of the window with the gray value median of each point in the window;
automatically selecting the best matching template according to the conditions of each pixel point on the image and 8 adjacent points around the pixel point to process, identify and judge so as to decide whether to reserve or filter;
for odd elements, the median refers to a numerical value in the middle after sorting according to size, and for even elements, the median refers to an average value of gray values of two middle elements after sorting;
the image is blurred by means of average and integral operation, and the image can be subjected to inverse operation by adopting a method of using a template and counting difference values by a differential operator, so that the image is enhanced and sharpened;
automatically transforming and correcting the coordinates of each pixel in the image by using a nearest neighbor gray interpolation method to obtain an original image after coordinate adjustment and a target classification image thereof, thereby obtaining a sequence two-dimensional slice image after registration;
setting the pixel (voxel) of the three-dimensional medical image in the gray scale range required for extracting the tissue as 1, and setting the rest as 0, namely, performing binary processing on the three-dimensional medical image by using two threshold values (d1, d 2):
assuming that the input image is f (x, y, z) and the output image is f' (x, y, z), then
Designing a color transfer function and an opacity transfer function, setting an imager and creating an imaging window based on mapping relation construction body data and setting attributes including a difference mode and illumination parameters;
adopting a GPU to perform ray projection algorithm imaging, initiating an interaction request, readjusting the interaction request if parameters change, and otherwise closing a window;
finding out a threshold range in the gray statistical histogram, dividing the original image into a plurality of regions, modifying the division result by opening and closing operations, and finally separating out a specific target;
further, the three-dimensional imaging module images the preprocessed medical slice into a three-dimensional stereo model, and realizes the segmentation of the specific tissue by using a segmentation method combining binarization and morphology and algorithms such as volume imaging or area imaging according to the requirements of doctors to realize the imaging of the specific tissue, and specifically comprises:
carrying out image intrusive scanning by adopting a laser excitation signal to generate an intrusive optical signal, and collecting the intrusive optical signal by using a data acquisition card;
the light outlet end of the multi-state optical cable is tightly attached to the light inlet end face of the self-focusing lens, is detected by an image converter in the guide pipe, is converted into an ultrasonic electric signal by mechanical waves, and is subjected to signal amplification processing by an ultrasonic transceiver;
diverging light beams transmitted and emitted from the optical cable converge after passing through the self-focusing lens and are transmitted to the surface of the sample through the transmission surface of the transmission mirror to excite the photoacoustic signal;
the main trigger excitation signal synchronously acts on the delay plate and completes the excitation and the collection of the optical signal after a certain time delay;
the image converter is tightly attached to the right-angle surface of the transmission mirror, and the detection surface of the image converter is vertically upward, so that the direction of a sound field receiving area is consistent with the direction of a reference line of a sample photoacoustic signal excitation surface;
the matching pipe and the base in the imaging guide pipe are used for assisting in assembling the guide pipe and arranging internal components, and the metal pipe is provided with an imaging window in the image converter and the transmission lens area;
when the program enters the execution state, the code performs each specified function on one hand, and simultaneously detects an end signal on the other hand, if a signal for requesting the end of the program is received, the program jumps out of the loop, simultaneously jumps out of the state machine structure, cleans up the program code, and exits the program.
Specifically, an MSP430 single chip microcomputer is used as a lower computer platform, and ports coming out of the single chip microcomputer are respectively connected with a 532 laser instrument and a rotary motor driver, and the rotary motor driver mainly plays a role in time delay triggering. The MSP430 receives the excitation signal trigger signal from the tunable laser, counts the excitation signal trigger signal, and outputs an excitation signal to trigger the tunable laser or the rotating machine driver to operate after a certain time delay when the count reaches a set value. Assuming the initial band mean of the tunable laser is λ1The mean value of the stop band is lambda2The scanning step length of the wave band mean value is S, and the number of laser excitation signals emitted under each wave band mean value is m. The number of counts Q of the MSP430 over a set of spectral cycles is then
After the MSP430 outputs the trigger excitation signal outwards, the original excitation signal is counted and cleared immediately, and a new round of counting is started, so that the spectrum mode that the photoacoustic spectrum is scanned in motion by the fixed-point spectrum is realized.
Further, the interventional interaction module adopts interactive volume data imaging, the user performs operations of rotating, zooming and translating on the imaged three-dimensional model, and the system displays the operation effect through the modules and can switch between different views, specifically comprising:
updating records in a record table according to the operation result, wherein each record in the record table comprises a hash value, an operation parameter and operation times; judging whether the operation times of the updated record reach a maximum threshold value or not, if so, deleting the record in the record table, and moving the hash value and the operation parameters in the record to the hash operation list as storage items to update the hash operation list;
the operation result is distributed on the grid points of the uniform grid or the regular grid, namely the structured data of the uniform grid or the structured data of the regular grid, and then the discrete operation result is subjected to format conversion, redundant data elimination, required data derivation and other operations;
classifying the three-dimensional data voxel according to the difference of the numerical values, and finding out the corresponding relation between the data and different substances or different attributes;
the hash value of the operation effect is a hash digest value of the effective content of the hit interactive object, the operation parameter represents an operation result of the data issued by the user corresponding to the effective content of the hit interactive object, and the operation frequency is the frequency of obtaining the operation result of the data issued by the user corresponding to the effective content of the hit interactive object.
The present invention is not limited to the above preferred embodiments, and any modifications, equivalent substitutions, improvements, etc. within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (5)
1. A scanning imaging system for interventional therapy, comprising:
the interventional therapy data reading module is responsible for reading in interventional therapy image data, supports image files in JPG and IMG formats besides files in DICOM format, unifies the image files into intermediate data in the same format, excites to obtain interventional therapy signals, and delivers the interventional therapy signals to the image preprocessing module for processing;
the image preprocessing module is used for preprocessing each slice of the medical data according to the operation of a user after the medical data transmitted by the interventional therapy data reading module is obtained, and the preprocessing comprises filtering, enhancing, registering, cutting a three-dimensional ultrasonic image, denoising and binaryzation;
the three-dimensional imaging module is used for imaging the preprocessed medical slice into a three-dimensional stereo model, and realizing the segmentation of a specific tissue by adopting a segmentation method combining binaryzation and morphology through algorithms such as volume imaging or surface imaging and the like according to the requirements of doctors so as to realize the imaging of the specific tissue;
the system comprises an interventional interactive module, a system and a display module, wherein the interventional interactive module adopts interactive volume data imaging, a user performs rotation, zooming and translation operations on an imaged three-dimensional model, and the system displays the operation effect through the modules and can switch among different views.
2. The scanning imaging system for interventional therapy as set forth in claim 1, comprising:
the interventional therapy data reading module is responsible for reading in interventional therapy image data, supports image files in JPG and IMG formats besides files in DICOM format, unifies the image files into intermediate data in the same format, excites and obtains interventional therapy signals, and sends the interventional therapy signals to the image preprocessing module for processing, and the interventional therapy data reading module comprises:
the digital image of the biological tissue and organ is obtained by scanning the interventional therapy image data through medical imaging equipment; interpolating between adjacent layers, representing the scanned interventional therapy image data as a sum of image information based on the interventional therapy image data in the sample library and interventional differentiation image information;
the data field is formed by the superposition of MRI and CT tomograms generated by a computer tomography scanner and nuclear magnetic resonance in one spatial direction;
obtaining interventional differentiation image information by utilizing parallel imaging, and forming sparse representation of scanned interventional treatment image data through a multi-coil model coefficient of the interventional image body and a coefficient of the interventional differentiation image information in a sparse transform domain;
the data field data is abstracted into a three-dimensional array obtained by uniformly sampling objects defined in a three-dimensional closed space, including organism tissues and organs;
constructing an interventional image volume according to the reference prior information, and capturing image information based on interventional treatment image data in a sample library through the interventional image volume;
interventional therapy image data jointly utilizing an interventional image volume, parallel imaging and an objective function enhanced sparse imaging scan.
3. The scanning imaging system for interventional therapy as set forth in claim 1, comprising:
the image preprocessing module is used for preprocessing each slice of the medical data according to the operation of a user after the medical data transmitted by the interventional therapy data reading module is obtained, wherein the preprocessing comprises filtering, enhancing, registering, three-dimensional ultrasonic image cutting, denoising and binaryzation, and specifically comprises the following steps:
adopting a sliding window containing odd points, and replacing the gray value of the central point of the window with the gray value median of each point in the window;
automatically selecting the best matching template according to the conditions of each pixel point on the image and 8 adjacent points around the pixel point to process, identify and judge so as to decide whether to reserve or filter;
for odd elements, the median refers to a numerical value in the middle after sorting according to size, and for even elements, the median refers to an average value of gray values of two middle elements after sorting;
the image is blurred by means of average and integral operation, and the image can be subjected to inverse operation by adopting a method of using a template and counting difference values by a differential operator, so that the image is enhanced and sharpened;
automatically transforming and correcting the coordinates of each pixel in the image by using a nearest neighbor gray interpolation method to obtain an original image after coordinate adjustment and a target classification image thereof, thereby obtaining a sequence two-dimensional slice image after registration;
setting the pixel of the three-dimensional medical image in the gray scale range required for extracting the tissue as 1, and setting the remaining pixel as 0, namely, performing binary processing on the three-dimensional medical image by using two thresholds (d1, d 2):
assuming that the input image is f (x, y, z) and the output image is f' (x, y, z), then
Designing a color transfer function and an opacity transfer function, setting an imager and creating an imaging window based on mapping relation construction body data and setting attributes including a difference mode and illumination parameters;
adopting a GPU to perform ray projection algorithm imaging, initiating an interaction request, readjusting the interaction request if parameters change, and otherwise closing a window;
finding out threshold range in the grey level histogram, dividing the original image into several areas, modifying the division result with opening and closing operation and separating out specific target.
4. The scanning imaging system for interventional therapy as set forth in claim 1, wherein:
the three-dimensional imaging module images the preprocessed medical slice into a three-dimensional stereo model, and realizes the segmentation of a specific tissue by using a segmentation method combining binarization and morphology and algorithms such as volume imaging or area imaging and the like according to the requirements of doctors to realize the imaging of the specific tissue, and the three-dimensional imaging module specifically comprises the following steps:
carrying out image intrusive scanning by adopting a laser excitation signal to generate an intrusive optical signal, and collecting the intrusive optical signal by using a data acquisition card;
the light outlet end of the multi-state optical cable is tightly attached to the light inlet end face of the self-focusing lens, is detected by an image converter in the guide pipe, is converted into an ultrasonic electric signal by mechanical waves, and is subjected to signal amplification processing by an ultrasonic transceiver;
diverging light beams transmitted and emitted from the optical cable converge after passing through the self-focusing lens and are transmitted to the surface of the sample through the transmission surface of the transmission mirror to excite the photoacoustic signal;
the main trigger excitation signal synchronously acts on the delay plate and completes the excitation and the collection of the optical signal after a certain time delay;
the image converter is tightly attached to the right-angle surface of the transmission mirror, and the detection surface of the image converter is vertically upward, so that the direction of a sound field receiving area is consistent with the direction of a reference line of a sample photoacoustic signal excitation surface;
the matching pipe and the base in the imaging guide pipe are used for assisting in assembling the guide pipe and arranging internal components, and the metal pipe is provided with an imaging window in the image converter and the transmission lens area;
when the program enters the execution state, the code performs each specified function on one hand, and simultaneously detects an end signal on the other hand, if a signal for requesting the end of the program is received, the program jumps out of the loop, simultaneously jumps out of the state machine structure, cleans up the program code, and exits the program.
5. The scanning imaging system for interventional therapy as set forth in claim 1, wherein:
the interventional interactive module adopts interactive volume data imaging, a user performs operations of rotating, zooming and translating on an imaged three-dimensional model, and a system displays the operation effect through the modules and can switch among different views, and the interactive module specifically comprises the following steps:
updating records in a record table according to the operation result, wherein each record in the record table comprises a hash value, an operation parameter and operation times; judging whether the operation times of the updated record reach a maximum threshold value or not, if so, deleting the record in the record table, and moving the hash value and the operation parameters in the record to the hash operation list as storage items to update the hash operation list;
the operation result is distributed on the grid points of the uniform grid or the regular grid, namely the structured data of the uniform grid or the structured data of the regular grid, and then the discrete operation result is subjected to format conversion, redundant data elimination, required data derivation and other operations; classifying the three-dimensional data voxel according to the difference of the numerical values, and finding out the corresponding relation between the data and different substances or different attributes;
the hash value of the operation effect is a hash digest value of the effective content of the hit interactive object, the operation parameter represents an operation result of the data issued by the user corresponding to the effective content of the hit interactive object, and the operation frequency is the frequency of obtaining the operation result of the data issued by the user corresponding to the effective content of the hit interactive object.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911120194.8A CN110827401B (en) | 2019-11-15 | 2019-11-15 | Scanning imaging system for interventional therapy |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911120194.8A CN110827401B (en) | 2019-11-15 | 2019-11-15 | Scanning imaging system for interventional therapy |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110827401A true CN110827401A (en) | 2020-02-21 |
| CN110827401B CN110827401B (en) | 2020-07-10 |
Family
ID=69555790
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911120194.8A Expired - Fee Related CN110827401B (en) | 2019-11-15 | 2019-11-15 | Scanning imaging system for interventional therapy |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110827401B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140031691A1 (en) * | 2011-04-14 | 2014-01-30 | Hitachi Aloka Medical, Ltd. | Ultrasound diagnostic device |
| CN104463965A (en) * | 2014-12-17 | 2015-03-25 | 中国科学院自动化研究所 | Training scene simulation system and method for minimally invasive cardiovascular interventional operation |
| CN104574263A (en) * | 2015-01-28 | 2015-04-29 | 湖北科技学院 | Quick three-dimensional ultrasonic reconstruction and display method on basis of GPU (graphics processing unit) |
| CN105551026A (en) * | 2015-12-08 | 2016-05-04 | 浙江工业大学 | Brain feature extraction method based on diffusion tensor imaging |
| CN107146262A (en) * | 2017-04-18 | 2017-09-08 | 清华大学深圳研究生院 | The three-dimensional visualization method and system of a kind of OCT image |
| CN110428887A (en) * | 2019-08-05 | 2019-11-08 | 河南省三门峡市中心医院(三门峡市儿童医院、三门峡市妇幼保健院) | A kind of brain tumor medical image three-dimensional reconstruction shows exchange method and system |
-
2019
- 2019-11-15 CN CN201911120194.8A patent/CN110827401B/en not_active Expired - Fee Related
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140031691A1 (en) * | 2011-04-14 | 2014-01-30 | Hitachi Aloka Medical, Ltd. | Ultrasound diagnostic device |
| CN104463965A (en) * | 2014-12-17 | 2015-03-25 | 中国科学院自动化研究所 | Training scene simulation system and method for minimally invasive cardiovascular interventional operation |
| CN104574263A (en) * | 2015-01-28 | 2015-04-29 | 湖北科技学院 | Quick three-dimensional ultrasonic reconstruction and display method on basis of GPU (graphics processing unit) |
| CN105551026A (en) * | 2015-12-08 | 2016-05-04 | 浙江工业大学 | Brain feature extraction method based on diffusion tensor imaging |
| CN107146262A (en) * | 2017-04-18 | 2017-09-08 | 清华大学深圳研究生院 | The three-dimensional visualization method and system of a kind of OCT image |
| CN110428887A (en) * | 2019-08-05 | 2019-11-08 | 河南省三门峡市中心医院(三门峡市儿童医院、三门峡市妇幼保健院) | A kind of brain tumor medical image three-dimensional reconstruction shows exchange method and system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110827401B (en) | 2020-07-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP4917733B2 (en) | Image registration system and method using likelihood maximization | |
| US10363010B2 (en) | Method for breast screening in fused mammography | |
| JP5014694B2 (en) | Method and apparatus for generating a multi-resolution framework for improving medical imaging workflow | |
| US20200367853A1 (en) | Apparatus for ai-based automatic ultrasound diagnosis of liver steatosis and remote medical diagnosis method using the same | |
| EP1398722A2 (en) | Computer aided processing of medical images | |
| GB2420641A (en) | Digital Medical Image Analysis | |
| WO2011015952A1 (en) | Method and system for stabilizing a series of intravascular ultrasound images and extracting vessel lumen from the images | |
| KR20140089669A (en) | Method, Apparatus and system for reducing speckles on image | |
| CN112070785A (en) | Medical image analysis method based on computer vision | |
| CN112950534A (en) | Portable ultrasonic pneumonia auxiliary diagnosis system based on artificial intelligence | |
| KR20210145003A (en) | Apparatus for restoring short scanning brain tomographic image using deep-learning | |
| CN110738633A (en) | organism tissue three-dimensional image processing method and related equipment | |
| US11510656B2 (en) | Ultrasound imaging method and ultrasound imaging system therefor | |
| CN110827401B (en) | Scanning imaging system for interventional therapy | |
| CA2854992C (en) | Process and apparatus for data registration | |
| KR101627319B1 (en) | medical image processor and method thereof for medical diagnosis | |
| KR101923962B1 (en) | Method for facilitating medical image view and apparatus using the same | |
| US20190172219A1 (en) | 3d image processing and visualization with anomalous identification and predictive auto-annotation generation | |
| CN111260606B (en) | Diagnostic device and diagnostic method | |
| CN116434918A (en) | Medical image processing method and computer readable storage medium | |
| Salehi et al. | Investigation and simulation of different medical image processing algorithms to improve image quality using simulink matlab | |
| US11410348B2 (en) | Imaging method and device | |
| Tamilkudimagal | Squeeze box filter for contrast enhancement in ultrasound despeckling | |
| Lin et al. | BSG-Net: A Blind Super-resolution Guided Network for Improving Ultrasound Image Segmentation | |
| Sendra-Balcells et al. | Generalisability of deep learning models in low-resource imaging settings: A fetal ultrasound study in 5 African countries |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20200616 Address after: 261500 West Gaomi City Town, Weifang City, Shandong Province, No. 77 Applicant after: Zhang Jun Applicant after: Song Ping Applicant after: Chen Ruiping Applicant after: Wei Hongmei Address before: 261500 West Gaomi City Town, Weifang City, Shandong Province, No. 77 Applicant before: Zhang Jun |
|
| TA01 | Transfer of patent application right | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20200710 |
|
| CF01 | Termination of patent right due to non-payment of annual fee |