CN106096322B - Liver and kidney medical image data cooperative processing system - Google Patents
Liver and kidney medical image data cooperative processing system Download PDFInfo
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Abstract
The invention discloses a liver and kidney medical image data cooperative processing system, which comprises: the system comprises a data processing center, a plurality of uploading user terminals and a plurality of downloading user terminals, wherein the plurality of uploading user terminals are connected with the data processing center through the Internet to upload initial data to the data processing center, and the plurality of downloading user terminals are connected with the data processing center through the Internet to download liver three-dimensional images or kidney three-dimensional images of the data processing center. The data processing center at least comprises an information database and a three-dimensional image processing module, wherein the three-dimensional image processing module is used for generating a three-dimensional image of a specific liver based on the CT image of the liver and a three-dimensional image of a specific kidney based on the CT image of the kidney, and the information database is used for storing the three-dimensional image of the specific liver from the three-dimensional image processing module according to the source information of the specific liver and storing the three-dimensional image of the specific kidney from the three-dimensional image processing module according to the source information of the specific kidney.
Description
Technical Field
The invention relates to a medical image processing system, in particular to a medical image three-dimensional visualization system.
Background
The three-dimensional reconstruction technology of the medical image can fully utilize medical image volume data such as CT, MRI and the like, and can obtain a three-dimensional projection image of perspective with any visual angle according to the needs by adopting an imaging algorithm of surface drawing or volume drawing, so that a doctor can observe the internal structure of a human body conveniently. The medical image is processed by utilizing a three-dimensional reconstruction technology, a three-dimensional model is constructed, the three-dimensional model is projected and displayed from different directions, the information of related organs is extracted, and a doctor can quantitatively describe the size, shape and spatial position of the organ of interest. The three-dimensional reconstruction technology enables doctors to intuitively and quantitatively view the three-dimensional structure of organs, and enhances various original details in images, thereby helping doctors to make more accurate diagnosis. By adopting the medical three-dimensional image reconstruction technology, a patient only needs to scan once to acquire data (original data) of a plurality of faults of the diseased part, and a doctor can observe from multiple angles through the technology, so that diagnosis is convenient. The doctor can observe the affected area from any angle and position, and can automatically analyze the information of the focus part, such as the position, the size and the like of tumors and thrombus by using a mode identification technology. The utility model reduces the working intensity of doctors, improves the working efficiency, and is beneficial to improving the modernization level of the medical industry.
Discrete data obtained by the traditional technology is processed and converted into an image with visual stereoscopic effect, and the three-dimensional state of tissues or organs is fully displayed, so that a plurality of anatomical structure information which cannot be obtained by the traditional means are provided. And this technique may provide a visual interaction basis for further developments in virtual techniques such as virtual speculum, virtual anatomy, etc. On the basis, computer simulation and operation planning of orthopedic operation, radiotherapy and the like can be realized.
Liver and kidney are important viscera for metabolism, detoxification, secretion and excretion of organism, and clinical two viscera are diseased simultaneously or sequentially, so that the relationship between the two viscera becomes an important issue for clinical attention research. The diseases of the liver and kidney may be independent of each other, or one disease may invade the liver and kidney at the same time, and sometimes it is the influence of pathological changes of one organ on the other organ. By reconstructing three-dimensional images of the liver and the kidney, the method is convenient for researching the relativity of the liver and the kidney of a human body, and has great significance for changing the current medical treatment mode by performing operation simulation aiming at specific etiology.
The medical image two-dimensional processing and three-dimensional reconstruction system disclosed in Chinese patent application 201310503694.6 comprises a data access module, a data management module, a display and visual area management module, a two-dimensional data preprocessing module, a two-dimensional data segmentation module, an interactive operation module and a three-dimensional reconstruction and visual adjustment module. The data access module is used for reading the medical image two-dimensional image file and storing the two-dimensional data into the magnetic disk after preprocessing, the data management module is used for planning and managing various data, and the display and visual area management module is used for displaying the two-dimensional image and the three-dimensional model and better displaying the two-dimensional image or the three-dimensional model in a visual area mode. The two-dimensional image preprocessing is used for carrying out adjustment processing such as gray level transformation, filtering, sharpening and the like on the original two-dimensional image with poor display effect, the interactive operation module is used for carrying out operations such as zooming, rotation, translation and the like on the image, the two-dimensional data segmentation module is used for extracting useful information to prepare for subsequent three-dimensional surface reconstruction, the three-dimensional reconstruction comprises surface reconstruction and point reconstruction, and the three-dimensional vision is adjusted to be the adjustment of three-dimensional model vision. However, the two-dimensional processing and three-dimensional reconstruction system of the medical image is not an open platform, and cannot share digital liver and kidney data and share knowledge.
As disclosed in chinese patent application 201310503694.6, a three-dimensional reconstruction method of liver CT image includes: segmenting the liver two-dimensional CT image sequence, and respectively extracting a segmentation sequence corresponding to each of a plurality of tissues of the liver; and reconstructing three-dimensional images of each tissue according to the segmentation sequence corresponding to each tissue and the three-dimensional reconstruction flow corresponding to each tissue so as to reconstruct three-dimensional liver CT images. However, the three-dimensional reconstruction method of the liver CT image cannot interactively display the three-dimensional CT stereoscopic image of the liver, and cannot process the liver and kidney data simultaneously to generate the three-dimensional CT stereoscopic image.
Therefore, the digital platform which can process liver data and kidney data simultaneously, realize real-time sharing and is suitable for wide popularization, can accurately search and is convenient for researching liver and kidney related diseases is a problem which is urgently needed to be solved in the industry.
Disclosure of Invention
The invention aims to provide a liver and kidney medical image data collaborative processing system which can realize the simultaneous processing of liver data and kidney data, realize real-time sharing and accurate retrieval and facilitate the study of liver and kidney related diseases by constructing a database platform.
According to an aspect of the present invention, there is provided a liver and kidney medical image data cooperative processing system comprising: the system comprises a data processing center, a plurality of uploading user terminals and a plurality of downloading user terminals. The data processing center is used for generating a liver three-dimensional image and a kidney three-dimensional image, the uploading user terminals are connected with the data processing center through the Internet to upload initial data to the data processing center, and the downloading user terminals are connected with the data processing center through the Internet to download the liver three-dimensional image or the kidney three-dimensional image of the data processing center. Each uploading user terminal at least comprises: the uploading system comprises an uploading type selection module for uploading user selection of uploading data types, a data input module for inputting liver CT images for specific livers or kidney CT images for specific kidneys into each uploading user terminal, a data preprocessing module for packing and compressing the CT images input by the data input module and source information of the specific livers or the specific kidneys into specific liver data packets or specific kidney data packets, and a data uploading module for uploading the specific liver data packets and the specific kidney data packets to a data processing center through the Internet. The data processing center at least comprises an information database and a three-dimensional image processing module, wherein the three-dimensional image processing module is used for generating a three-dimensional image of a specific liver based on the CT image of the liver and a three-dimensional image of a specific kidney based on the CT image of the kidney, and the information database is used for storing the three-dimensional image of the specific liver from the three-dimensional image processing module according to the source information of the specific liver and storing the three-dimensional image of the specific kidney from the three-dimensional image processing module according to the source information of the specific kidney. Each downloading user terminal at least comprises a login retrieval module and a data downloading module, wherein the login retrieval module is arranged on each downloading user terminal and used for logging in a data processing center through a specific registered user account through the Internet so as to retrieve and browse specific liver three-dimensional images or specific kidney three-dimensional images in an information database, the data downloading module is arranged on each downloading user terminal, and a downloading user selects and downloads a required downloading three-dimensional reconstruction image type through the data downloading module.
Optionally, the uploading type selecting module of each uploading user terminal comprises a liver data uploading subunit and a kidney data uploading subunit.
Optionally, the liver CT images uploaded by the data input module of the uploading user terminal are at least 100 liver CT images in DICOM format of different cross sections for a specific liver, and the kidney CT images uploaded by the data input module of the uploading user terminal are at least 30 kidney CT images in DICOM format of different cross sections for a specific kidney, preferably 100.
The uploading user terminal can be an authorized multifunctional CT device or computer of a designated hospital, and a doctor can log in the data processing center through the uploading user terminal by uploading a user account number to upload or download liver CT images or kidney CT images.
The downloading user terminal can be any personal computer, and a common user logs in the data processing center through the downloading user terminal by the downloading user account number so as to search, browse or download liver CT images or kidney CT images.
The data processing center can be a data processing platform built based on a plurality of servers and a plurality of storage devices.
Optionally, the source information of the specific liver and the specific kidney at least comprises: the type of illness, the sex of the patient, the age of the patient, the region of life, and the hospital visit, wherein the source information of the specific kidney further includes the left kidney or the right kidney.
Optionally, the source information of the specific liver and the specific kidney may further comprise: patient lifestyle, biochemical examination information, patient typical symptoms, signs, medical images, imaging diagnosis results, treatment schemes, adverse reactions, attending physicians, and the like.
Optionally, the data downloading module is further disposed on each uploading user terminal and is used for downloading the specific liver three-dimensional image or the specific kidney three-dimensional image in the information database to the uploading user terminal through the internet.
Optionally, a login retrieval module is further disposed on each uploading user terminal and is used for logging in the data processing center through the internet so that the uploading user can retrieve, browse or use the specific liver three-dimensional image or the specific kidney three-dimensional image in the information database.
Optionally, the liver and kidney medical image data collaborative processing system further includes a user communication module, and the user communication module is disposed on each uploading user terminal and each downloading user terminal, and is used for the uploading user and the downloading user to respectively perform communication analysis on the specific liver three-dimensional image or the specific kidney image through the internet.
Alternatively, each uploading user or each downloading user may communicate with one or more uploading and downloading users through the user communication module.
The three-dimensional image processing module of the data processing center comprises a liver three-dimensional processing sub-module for carrying out liver three-dimensional reconstruction according to each liver CT image to obtain a specific liver three-dimensional image and a kidney three-dimensional processing sub-module for carrying out kidney three-dimensional reconstruction according to each kidney CT image to obtain a specific kidney three-dimensional image.
Optionally, the liver three-dimensional processing sub-module further comprises a liver image preprocessing unit, a liver extraction unit and a liver three-dimensional image drawing unit. The liver image preprocessing unit sequentially performs image smoothing and image enhancement processing on each liver CT image in the liver CT images, the liver extraction unit segments the preprocessed liver data images to detect liver contour edges and extract liver contour lines, and the liver three-dimensional image drawing unit performs surface reconstruction on the liver according to the liver contour lines obtained from each liver CT image to obtain a specific liver three-dimensional image.
The liver image preprocessing unit of the liver three-dimensional processing sub-module further comprises: an image smoothing subunit and an image enhancement subunit. The image smoothing subunit directly carries out operation processing on the pixel gray value of each liver CT image in a spatial domain by adopting a airspace method, and filters noise in each liver CT image. And an image enhancement subunit for sharpening and enhancing each liver CT image subjected to the smoothing processing to increase the edge sharpness of each liver CT image.
Alternatively, the image smoothing subunit may perform smoothing on each liver CT image, and may select a neighborhood averaging method or a median filtering method.
Alternatively, the image enhancement unit may perform enhancement processing on each liver CT image only concerning the position of the edge point regardless of the actual gray level difference around it, and may perform enhancement processing on the image using a differential sharpening method, such as a laplace sharpening method.
Optionally, the liver extraction unit further comprises: a liver localization subunit, a liver segmentation subunit, a boundary detection subunit, and a boundary tracking subunit.
The liver positioning subunit automatically positions the liver position in each liver CT image through the volume and the gray level of the liver. The liver segmentation subunit registers each liver CT image output by the liver image preprocessing unit, and segments each liver CT image to obtain segmented liver part images. The boundary detection subunit inspects the change of gray level of each pixel in the segmented liver part image in any neighborhood by a differential operator method, and locates liver boundary points according to the change of first-order and/or second-order directional derivative of any neighborhood of each pixel. The boundary tracking subunit sequentially searches adjacent liver boundary points and sequentially connects the boundary points so as to gradually detect the liver boundary to obtain the determined liver contour.
Optionally, after the liver segmentation subunit segments to obtain segmented liver part images, a hole filling algorithm is adopted to remove tiny holes and wrong connection generated in the segmentation process of the segmented liver part images, then a region growing method is adopted to remove redundant tissues of the segmented liver part images, the internal holes of the segmented liver part images are further filled, and finally contour correction is carried out.
Optionally, the liver three-dimensional image drawing unit further includes: the device comprises a contour matching subunit, a contour splicing processing subunit, a contour interpolation subunit and a surface fitting subunit. The contour matching subunit searches for and matches the sequential relationship among the liver contours of different sections in the liver contours of different sections respectively determined by the liver CT images by calculating the area of the liver contour obtained by the boundary tracking unit of the liver extraction unit. The contour splicing processing subunit adopts a triangular surface patch method to construct the surfaces among the liver contours with different sections so as to obtain a liver two-dimensional tomographic image; the contour interpolation subunit interpolates between adjacent liver two-dimensional tomographic images to realize transition of structures between the images of each layer. The curved surface fitting subunit smoothes a curved surface between two-dimensional tomographic images of the liver by adopting an interpolation method or an approximation method, and fits the two-dimensional tomographic images of the liver to form a final reconstructed curved surface so as to obtain a three-dimensional CT image of the specific liver.
Optionally, the liver three-dimensional image rendering unit further comprises a contour bifurcation processing subunit. The contour bifurcation processing subunit adopts topology and geometric structure to process the liver two-dimensional tomographic image which is interpolated and transited by the contour stitching processing subunit, so as to solve the problem that the corresponding relation of the liver contour is uncertain due to local information generated by bifurcation. Alternatively, the boundary detection subunit of the liver extraction unit may locate the liver boundary point by using methods such as Sobel operator, roberts operator, and Kirsch operator.
Optionally, the kidney three-dimensional processing sub-module further includes a kidney image preprocessing unit, a kidney extraction unit, and a kidney three-dimensional image drawing unit. The image preprocessing sub-module reads a series of kidney CT images and sequentially carries out image smoothing and image enhancement processing on each kidney CT image, the kidney extraction unit segments the preprocessed kidney data images to detect kidney contour edges and extract kidney contour lines, and the kidney three-dimensional image drawing unit carries out surface reconstruction on the kidneys according to the kidney contour lines obtained by each kidney CT image to obtain a specific kidney three-dimensional image.
The image preprocessing unit of the kidney three-dimensional processing sub-module further comprises: an image smoothing subunit and an image enhancement subunit. The image smoothing subunit directly carries out operation processing on pixel gray values of each kidney CT image in a spatial domain by adopting a airspace method, and filters noise in each kidney CT image. The image enhancement subunit is used for sharpening and enhancing each kidney CT image subjected to the smoothing treatment so as to increase the edge sharpness of each kidney CT image.
Alternatively, the image smoothing subunit may perform smoothing on each kidney CT image by selecting a neighborhood averaging method or a median filtering method.
Alternatively, the image enhancement subunit may perform enhancement processing on each renal CT image by using differential sharpening, such as laplace sharpening, on the image, where the enhancement processing is performed on each renal CT image only with respect to the location of the edge point, regardless of the actual gray level difference around the edge point.
Optionally, the kidney extraction unit further comprises: kidney subunit, kidney segmentation subunit, boundary detection subunit, and boundary tracking subunit. The kidney positioning subunit automatically positions the kidney position in each kidney CT image through the kidney volume and the kidney gray scale. The kidney segmentation subunit registers each kidney CT image output by the preprocessing submodule, and segments each kidney CT image to obtain segmented kidney part images. The boundary detection subunit inspects the gray level change of each pixel in the segmented kidney part image in any neighborhood by a differential operator method, and locates kidney boundary points according to the first-order and/or second-order derivative change of any neighborhood of each pixel. The boundary tracking subunit sequentially searches adjacent kidney boundary points and sequentially connects the boundary points so as to gradually detect kidney boundaries and obtain a determined kidney contour.
Optionally, after the kidney segmentation subunit segments to obtain segmented kidney part images, a hole filling algorithm is adopted to remove tiny holes and wrong connection generated in the segmentation process of the segmented kidney part images, then a region growing method is adopted to remove redundant tissues of the segmented kidney part images, the internal holes of the segmented kidney part images are further filled, and finally contour correction is carried out.
Alternatively, the boundary detection subunit may locate the kidney boundary point by using the methods of Sobel operator, roberts operator, kirsch operator, and the like.
Optionally, the step of determining the kidney contour by the boundary tracking subunit comprises: and finding out the 1 st boundary point of the segmented kidney part image as a starting boundary point. With this starting boundary point as a starting point, a specific direction is tracked based on the feature that the boundaries of the image should be continuous. Specifically, starting from the found 1 st boundary point, defining an initial searching direction as along the lower left, if the pixel point at the lower left is the boundary point, adding the pixel point into a boundary chain table, and darkening the pixel point to represent the boundary point; otherwise the tracking direction is rotated 45 degrees counter-clockwise. Thus, a new boundary point is always found, then the search direction is rotated clockwise by 90 degrees on the basis of the current tracking direction, and the next boundary point is continuously tracked by the same method until the starting boundary point is returned, so that the kidney profile is obtained.
Alternatively, the boundary tracking subunit may also select to manually extract the kidney contour, select points with obvious changes in the segmented kidney part image as feature points, and perform smoothing treatment after connecting into fold lines to obtain the kidney contour.
Optionally, the kidney three-dimensional image drawing unit further includes: the contour matching subunit and the MC reconstruction subunit. The contour matching subunit sets the value of the isosurface, extracts the target contour, calculates the area of the kidney contour obtained by the boundary tracking unit of the kidney extraction subunit, and searches for and matches the sequence relationship among the kidney contours of different sections in the kidney contours of different sections respectively determined by the kidney CT images. The MC reconstruction subunit reads two initial kidney contours for the first time, then reads an adjacent slice each time, wherein four adjacent pixel points in pixel points on each slice and four corresponding pixel points of the next slice form a cube, the cube is called a voxel, all adjacent cubes in one layer are sequentially processed from left to right and from front to back, boundary voxels are judged, an isosurface is extracted, the next slice is read continuously after the first layer is processed, the isosurface is extracted after all slices are processed, and the algorithm is finished to obtain the specific kidney three-dimensional image.
The MC reconstruction subunit obtains its internal iso-surface from each voxel using the MC algorithm as follows: each voxel has eight vertices whose gray values are directly obtainable from the pixel values of the input slice, and the threshold value of the iso-surface to be extracted also requires a user to give in advance before calculation. Of these eight vertices, we mark vertices with gray values greater than a given threshold as black, while vertices with gray values less than the threshold are not marked.
Obviously if there are both "marked" and "unmarked" points in a cube, then there must be iso-surfaces within the cube. Except for the case where all labeled and all labeled voxels do not contain an isosurface, there may be both "labeled" and "unlabeled" states for 8 vertices in a voxel cube, and if the location of the isosurface on the cube edge is not considered, there may be 256 total distribution of isosurfaces on a voxel. The situation of rotational symmetry in the cube can be removed because the topological structure of the isosurface is not affected after the cube rotates. In addition, all "unlabeled" and "marked" can be interchanged, so that the topology of the iso-surface is not changed. Thus, only 15 base cubes are needed to represent all 256 possible scenarios. These 15 cases are constructed as an index table of length 256, which records 256 possible connection ways of the isosurface within a voxel. After the marking condition of eight vertexes is obtained, an index value between 0 and 15 is obtained according to the marking condition, then the index table is directly compared according to the index value, so that the edge of the voxel cube on which the equivalent point is positioned can be known, the connection mode of the equivalent point in the voxel can be obtained from the index table, and the equivalent points can be connected to form an equivalent surface at the moment.
Alternatively, the kidney three-dimensional image rendering unit may render a specific kidney three-dimensional image entity by defining specified scene illumination, viewing angle, and focus information.
Preferably, the liver and kidney medical image data cooperative processing system further comprises a dynamic demonstration module, and the dynamic demonstration module is arranged in the data processing center. The dynamic demonstration module comprises an interactive display unit and a windowing unit. The interactive display unit is used for providing entity display and interaction of the three-dimensional images of the specific liver and the specific kidney. The windowing unit constructs a cutting plane through cutting vertexes which are freely arranged on three-dimensional images of the specific liver and the specific kidney, the position of each cutting plane is moved through mouse operation to display different windowing effects, any fault of the three-dimensional images of the specific liver or the three-dimensional images of the specific kidney is reproduced, and the internal structure of the three-dimensional CT images of the specific liver or the three-dimensional CT images of the specific kidney is displayed.
Optionally, the dynamic demonstration module performs the interactive operations of moving, rotating and positioning by setting the cutting direction and the cutting point in combination with the cutting plane, so as to realize the excision of any direction and any position of the three-dimensional images of the specific liver and the three-dimensional images of the specific kidney.
The liver segmentation subunit registers each liver CT image output by the preprocessing submodule and the kidney segmentation subunit registers each kidney CT image output by the preprocessing submodule as follows: analyzing the CT image, extracting characteristic points of the CT image and storing the characteristic points as datum points; selecting a CT image as a reference image, wherein the CT image selected as the reference image is preferably a CT image with small offset and clear image; searching for adjacent images of the reference image according to the characteristic points of the images; determining spatial transformation according to the corresponding feature points; moving the reference image and performing iterative operation; and (5) saving the calculation result until the iteration is completed and finishing the registration process of the whole sequence image.
According to another aspect of the present invention, there is provided a liver and kidney medical image data cooperative processing system comprising: the system comprises a data processing center station, a plurality of uploading user terminals and a plurality of downloading user terminals, wherein the plurality of uploading user terminals are connected with the data processing center station through a wired or wireless network, and the plurality of downloading user terminals are connected with the data processing center station through the wired or wireless network. And each uploading user terminal is at least provided with an uploading type selection module, a data input module, a preliminary processing module and a data uploading module which are sequentially arranged according to the information processing sequence. The data processing center station is at least provided with three-dimensional image processing modules and information database units which are sequentially arranged according to the information processing sequence. Each downloading user terminal is at least provided with a login retrieval module and a data downloading module which are respectively connected with the information database unit of the data processing center station.
Optionally, the uploading type selecting module of each uploading user terminal comprises a liver data uploading subunit and a kidney data uploading subunit which are separately arranged.
Preferably, each uploading user terminal is further provided with a data downloading module for establishing data connection with the information database unit of the data processing center station.
Each uploading user terminal is further provided with a login retrieval module which establishes data connection with the information database unit of the data processing center station.
Preferably, each uploading user terminal and each downloading user terminal are further respectively provided with a user communication module.
The three-dimensional image processing module of the data processing center station comprises a liver three-dimensional processing sub-module and a kidney three-dimensional processing sub-module which are arranged separately.
Optionally, at least a liver image preprocessing unit, a liver extraction unit and a liver three-dimensional image drawing unit which are sequentially arranged according to the information processing sequence are arranged on the liver three-dimensional processing sub-module.
Optionally, at least a kidney image preprocessing unit, a kidney extraction unit and a kidney three-dimensional image drawing unit which are sequentially arranged according to the information processing sequence are arranged on the kidney three-dimensional processing sub-module.
The beneficial effects of the invention are as follows: (1) The liver and kidney medical image data collaborative processing system can simultaneously process liver data and kidney data; (2) The liver and kidney data are shared in real time, and related liver and kidney pathology researches in medicine are performed; (3) The liver and kidney medical image data cooperative processing system intensively processes a large amount of liver data and kidney data, so that a large amount of processing work is saved, and the resource sharing and searching are convenient, thereby being suitable for popularization and application; (4) The system comprises a large amount of liver data and kidney data, and through open platform sharing, global experts can share digital data and discuss cases, so that the doctor can communicate with each other, knowledge sharing is facilitated, and the national internet and strategy direction is met.
Drawings
Fig. 1 is a schematic diagram showing the construction of a liver and kidney medical image data cooperative processing system according to a first embodiment of the present invention.
Detailed Description
Referring to fig. 1, according to a first embodiment of the present invention, there is provided a liver and kidney medical image data collaborative processing system, including: a number of uploading user terminals 100, a data processing center 200 and a number of downloading user terminals 300. Several uploading user terminals 100 are connected with the data processing center 200 through the internet to upload initial data to the data processing center 200. The data processing center 200 is used to generate three-dimensional images of the liver and three-dimensional images of the kidneys. Several download user terminals 300 are connected to the data processing center 200 through the internet to download three-dimensional images of the liver or kidney of the data processing center 200.
Each uploading user terminal 100 comprises an uploading type selection module 110, a data input module 130, a data pre-processing module 140, a data uploading module 150.
The upload type selection module 110 is configured to upload a user selected upload data type, and the upload type selection module 110 includes a liver data upload subunit (not shown) and a kidney data upload subunit (not shown). The data input module 130 is configured to input a liver CT image for a specific liver or a kidney CT image 50-100 for a specific kidney into each uploading user terminal 100, the liver CT image uploaded by the data input module 130 is 50-100 liver CT images in DICOM format of different cross sections for the specific liver, and the kidney CT image uploaded by the data input module of the uploading user terminal is 50-100 kidney CT images in DICOM format of different cross sections for the specific kidney. The data pre-processing module 140 is configured to package and compress the CT images of the liver and the kidney input by the data input module and source information of the specific liver and the kidney into a specific liver data packet or a specific kidney data packet, and the data uploading module 150 is configured to upload the specific liver data packet and the specific kidney data packet to the data processing center 200 through the internet.
The data processing center 200 includes a three-dimensional image processing module 210 for generating a specific liver three-dimensional image based on a liver CT image and a specific kidney three-dimensional image based on a kidney CT image, and an information database 230. The data processing center 200 is a data processing platform built based on a plurality of servers and a plurality of storage devices.
The information database 230 is used for storing the three-dimensional images of the specific liver from the three-dimensional image processing module 210 according to the source information classification of the specific liver and storing the three-dimensional images of the specific kidney from the three-dimensional image processing module 210 according to the source information classification of the specific kidney.
Each download user terminal 300 includes a login retrieval module 310 and a data download module 330. A login retrieval module 310 is provided on each download user terminal 300 for logging in the data processing center 200 through the internet with a specific registered user account to retrieve, browse a specific liver three-dimensional image or a specific kidney three-dimensional image in the information database 230, and a data download module 330 is provided on each download user terminal 300, and a download user selects and downloads a desired download three-dimensional reconstruction image type through the data download module 330.
The three-dimensional image processing module 210 of the data processing center 200 includes a liver three-dimensional processing sub-module 213 that performs three-dimensional reconstruction of the liver according to each liver CT image to obtain a specific liver three-dimensional image, and a kidney three-dimensional processing sub-module 215 that performs three-dimensional reconstruction of the kidney according to each kidney CT image to obtain a specific kidney three-dimensional image.
The liver three-dimensional processing sub-module 213 further includes a liver image preprocessing unit (not shown), a liver extraction unit (not shown), and a liver three-dimensional image drawing unit (not shown). The liver three-dimensional image drawing unit includes: the method comprises the steps of respectively searching for a liver contour matching subunit which is matched with the sequential relation among liver contours of different sections by calculating the areas of the liver contours, constructing the surfaces among the liver contours of different sections by adopting a triangular surface patch method to obtain a contour mosaic processing subunit of a liver two-dimensional tomographic image, interpolating between adjacent liver two-dimensional tomographic images to realize the contour interpolation subunit of the transition of structures among images of each layer, and fitting the liver two-dimensional tomographic images to form a final reconstruction curved surface to obtain a curved surface fitting subunit of a specific liver three-dimensional CT image.
The kidney three-dimensional processing sub-module includes a kidney image preprocessing unit 215, a kidney extraction unit (not shown), and a kidney three-dimensional image drawing unit (not shown). The kidney three-dimensional image drawing unit includes: the kidney contour matching subunit and the MC reconstruction subunit. The kidney contour matching subunit sets the value of the isosurface, extracts the target contour, calculates the area of the kidney contour, and searches and matches the sequence relation among the kidney contours with different sections in the kidney contours with different sections. The MC reconstruction subunit reads two initial kidney contours for the first time, then reads an adjacent slice each time, wherein four adjacent pixel points in pixel points on each slice and four corresponding pixel points of the next slice form a cube, the cube is called a voxel, all adjacent cubes in one layer are sequentially processed from left to right and from front to back, boundary voxels are judged, an isosurface is extracted, the next slice is read continuously after the first layer is processed, the isosurface is extracted after all slices are processed, and the algorithm is finished to obtain the specific kidney three-dimensional image.
In this non-limiting embodiment, the uploading user terminal 100 is an authorized multi-function CT device or computer for a given hospital, and the physician can log into the data processing center 200 through the uploading user terminal 100 by uploading the user account number to upload or download liver CT images or kidney CT images.
In this non-limiting embodiment, the downloading user terminal 300 may be any personal computer, and the general user logs into the data processing center 200 at the downloading user terminal 300 by downloading a user account to retrieve, browse or download liver CT images or kidney CT images.
As an alternative embodiment, each uploading user terminal 100 is further provided with a data downloading module 170, which is configured to download the specific liver three-dimensional image or the specific kidney three-dimensional image in the information database 230 to the uploading user terminal 100 through the internet.
As an alternative implementation manner, each uploading user terminal 100 is further provided with a login retrieval module 180, which is used for logging into the data processing center 200 through the internet so that the uploading user can retrieve and browse the specific liver three-dimensional image or the specific kidney three-dimensional image in the information database 230.
As an alternative implementation manner, each uploading user terminal is further provided with a user communication module 190, and each downloading user terminal is further provided with a user communication module 350, so that the uploading user and the downloading user can respectively perform communication analysis on a specific liver three-dimensional image or a specific kidney image through the internet.
As an alternative embodiment four, the source information of the specific liver and the specific kidney each includes: the type of illness, the sex of the patient, the age of the patient, the region of life, and the hospital visit, wherein the source information of the specific kidney further includes the left kidney or the right kidney.
As an alternative embodiment, the liver and kidney medical image data collaborative processing system further includes a dynamic presentation module 150, and the dynamic presentation module 250 is disposed in the data processing center 200. The dynamic presentation module 250 includes an interactive display unit (not shown) and a windowing unit (not shown). The interactive display unit is used for providing entity display and interaction of the three-dimensional images of the specific liver and the specific kidney. The windowing unit constructs a cutting plane through cutting vertexes which are freely arranged on three-dimensional images of the specific liver and the specific kidney, the position of each cutting plane is moved through mouse operation to display different windowing effects, any fault of the three-dimensional images of the specific liver or the three-dimensional images of the specific kidney is reproduced, and the internal structure of the three-dimensional CT images of the specific liver or the three-dimensional CT images of the specific kidney is displayed. And the dynamic demonstration module is used for realizing the excision of any direction and any position of the specific kidney three-dimensional image by setting the incision direction and the incision point and combining the cutting plane to carry out the interactive operation of movement, rotation and positioning.
Although preferred embodiments of the present invention have been described in detail herein, it is to be understood that the invention is not limited to the precise construction herein described and illustrated, and that other modifications and variations may be effected by one skilled in the art without departing from the spirit and scope of the invention.
Claims (1)
1. A liver and kidney medical image data co-processing system, comprising:
the data processing center is used for generating a liver three-dimensional image and a kidney three-dimensional image;
the uploading user terminals are connected with the data processing center through the Internet to upload initial data to the data processing center;
the downloading user terminals are connected with the data processing center through the Internet to download the liver three-dimensional image or the kidney three-dimensional image of the data processing center;
the method is characterized in that: each uploading user terminal at least comprises: an upload type selection module for uploading user selection of upload data type, a data input module for inputting liver CT image for a specific liver or kidney CT image for a specific kidney to each of the upload user terminals, a data pre-processing module for packing and compressing CT image input by the data input module and source information of the specific liver or the specific kidney into a specific liver data packet or a specific kidney data packet, and a data upload module for uploading the specific liver data packet and the specific kidney data packet to the data processing center through the internet;
The data processing center at least comprises an information database and a three-dimensional image processing module, wherein the three-dimensional image processing module is used for generating a specific liver three-dimensional image based on the liver CT image and a specific kidney three-dimensional image based on the kidney CT image, and the information database is used for storing the specific liver three-dimensional image from the three-dimensional image processing module according to the source information of the specific liver and storing the specific kidney three-dimensional image from the three-dimensional image processing module according to the source information of the specific kidney;
the data processing center is a data processing platform built based on a plurality of servers and a plurality of storage devices;
each downloading user terminal at least comprises a login retrieval module and a data downloading module, wherein the login retrieval module is arranged on each downloading user terminal and used for logging in the data processing center through a registered user account through the Internet so as to retrieve and browse a specific liver three-dimensional image or a specific kidney three-dimensional image in the information database, and the data downloading module is arranged on each downloading user terminal, and a downloading user selects and downloads a required three-dimensional reconstruction image type through the data downloading module;
The uploading type selection module of each uploading user terminal comprises a liver data uploading subunit and a kidney data uploading subunit;
the liver CT images uploaded by the data input module of the uploading user terminal are at least 100 liver CT images in DICOM formats of different cross sections of specific livers, and the kidney CT images uploaded by the data input module of the uploading user terminal are at least 30 kidney CT images in DICOM formats of different cross sections of specific kidneys;
the source information of the specific liver and the specific kidney at least comprises: the type of illness, the sex of the patient, the age of the patient, the region of life, and the hospital of visit, wherein the source information of the specific kidney further includes the left kidney or the right kidney;
the data downloading module is further arranged on each uploading user terminal and used for downloading the specific liver three-dimensional image or the specific kidney three-dimensional image in the information database to the uploading user terminal through the Internet;
the login retrieval module is further arranged on each uploading user terminal and used for logging in the data processing center through the Internet so that an uploading user can retrieve and browse a specific liver three-dimensional image or a specific kidney three-dimensional image in the information database;
The system comprises a user communication module, wherein the user communication module is arranged on each uploading user terminal and each downloading user terminal and is used for respectively carrying out communication analysis on a specific liver three-dimensional image or a specific kidney image by an uploading user and a downloading user through the Internet;
the three-dimensional image processing module of the data processing center comprises a liver three-dimensional processing sub-module for carrying out liver three-dimensional reconstruction according to each liver CT image to obtain a specific liver three-dimensional image and a kidney three-dimensional processing sub-module for carrying out kidney three-dimensional reconstruction according to each kidney CT image to obtain a specific kidney three-dimensional image;
the liver three-dimensional processing sub-module further comprises a liver image preprocessing unit, a liver extraction unit and a liver three-dimensional image drawing unit, wherein the liver three-dimensional image drawing unit comprises: the method comprises the steps of respectively searching for a liver contour matching subunit which is matched with the sequential relation among liver contours of different sections by calculating the areas of the liver contours, constructing the surfaces among the liver contours of different sections by adopting a triangular surface patch method to obtain a contour mosaic processing subunit of a liver two-dimensional tomographic image, interpolating between adjacent liver two-dimensional tomographic images to realize the contour interpolation subunit of the transition of structures among images of each layer, and fitting the liver two-dimensional tomographic images to form a final reconstruction curved surface to obtain a curved surface fitting subunit of a specific liver three-dimensional CT image;
The liver image preprocessing unit of the liver three-dimensional processing sub-module further comprises: an image smoothing subunit and an image enhancement subunit; the image smoothing subunit directly carries out operation processing on the pixel gray value of each liver CT image in a spatial domain by adopting a airspace method, and filters noise in each liver CT image; and the image enhancement subunit is used for sharpening and enhancing each liver CT image subjected to the smoothing treatment so as to increase the edge definition of each liver CT image;
the image smoothing subunit performs smoothing treatment on each liver CT image and selects a neighborhood average method or a median filtering method;
the image enhancement subunit carries out enhancement processing on each liver CT image only concerning the position of an edge point and not concerning the actual gray level difference around the edge point, and adopts a differential sharpening method to carry out enhancement processing on the image in the image enhancement unit;
the kidney three-dimensional processing sub-module further comprises a kidney image preprocessing unit, a kidney extraction unit and a kidney three-dimensional image drawing unit, wherein the kidney three-dimensional image drawing unit comprises: the kidney contour matching subunit is used for setting values of isosurfaces, extracting target contours, calculating areas of the kidney contours, and searching and matching sequence relations among the kidney contours with different sections in the kidney contours with different sections; the MC reconstruction subunit reads two initial kidney contours for the first time, reads an adjacent slice at a time later, forms a voxel by four adjacent pixel points in each slice and four corresponding pixel points of the next slice, sequentially processes all adjacent voxels in one layer from left to right and from front to back, judges boundary voxels, extracts an isosurface, then transfers to the first step after finishing processing one layer, continues to read the next slice, extracts the isosurface after finishing processing all slices, and finishes the algorithm to obtain the specific kidney three-dimensional image;
The kidney extraction unit further comprises: a kidney positioning subunit, a kidney segmentation subunit, a boundary detection subunit, and a boundary tracking subunit; the kidney positioning subunit automatically positions the kidney position in each kidney CT image according to the kidney volume and the kidney gray scale; the kidney segmentation subunit registers each kidney CT image output by the preprocessing submodule, and segments each kidney CT image to obtain a segmented kidney part image; the boundary detection subunit inspects the change of gray level of each pixel in the segmented kidney part image in any neighborhood by a differential operator method, and locates kidney boundary points according to the change of first-order and/or second-order directional derivative of any neighborhood of each pixel; the boundary tracking subunit sequentially searches adjacent kidney boundary points and sequentially connects the boundary points so as to gradually detect kidney boundaries and obtain a determined kidney contour;
after the kidney segmentation subunit segments to obtain segmented kidney part images, a hole filling algorithm is adopted to remove tiny holes and error connection generated in the segmentation process of the segmented kidney part images, then a region growing method is adopted to remove redundant tissues of the segmented kidney part images, the internal holes of the segmented kidney part images are further filled, and finally contour correction is carried out;
The boundary detection subunit locates kidney boundary points through Sobel operator, roberts operator and Kirsch operator methods;
the boundary tracking subunit determines the kidney contour line by the steps of: finding out the 1 st boundary point of the segmented kidney part image as an initial boundary point; tracking a specific direction by taking the initial boundary point as a starting point according to the characteristic that the boundary of the image is continuous; starting from the found 1 st boundary point, defining an initial searching direction as along the lower left, if the pixel point at the lower left is the boundary point, adding the pixel point into a boundary chain table, and blackening the pixel point to represent the boundary point; otherwise, the tracking direction rotates anticlockwise for 45 degrees, so that a new boundary point is always found, then the searching direction rotates clockwise for 90 degrees on the basis of the current tracking direction, and the next boundary point is continuously tracked by the same method until the starting boundary point is returned, so that the kidney profile is obtained;
the liver and kidney medical image data cooperative processing system further comprises a dynamic demonstration module, wherein the dynamic demonstration module is arranged in the data processing center; the dynamic demonstration module comprises an interactive display unit and a windowing unit; the interactive display unit is used for providing entity display and interaction of the three-dimensional images of the specific liver and the specific kidney; the window opening unit is used for constructing a cutting plane through cutting vertexes which are freely arranged on three-dimensional images of the specific liver and the specific kidney, moving the position of each cutting plane through mouse operation to show different window opening effects, reproducing any fault of the three-dimensional images of the specific liver or the three-dimensional images of the specific kidney, and displaying the internal structure of the three-dimensional CT images of the specific liver or the three-dimensional CT images of the specific kidney; the dynamic demonstration module is used for realizing the excision of any direction and any position of a specific liver three-dimensional image and a specific kidney three-dimensional image by setting a cutting-in direction and a cutting-in point and combining with a cutting plane to carry out moving, rotating and positioning interactive operation;
The kidney segmentation subunit registers each kidney CT image output by the preprocessing submodule as follows: analyzing the CT image, extracting characteristic points of the CT image and storing the characteristic points as datum points; selecting a CT image as a reference image; searching for adjacent images of the reference image according to the characteristic points of the images; determining spatial transformation according to the corresponding feature points; moving the reference image and performing iterative operation; and (5) saving the calculation result until the iteration is completed and finishing the registration process of the whole sequence image.
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