CN111667903A - Medical image processing method and device - Google Patents
Medical image processing method and device Download PDFInfo
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- CN111667903A CN111667903A CN202010331281.4A CN202010331281A CN111667903A CN 111667903 A CN111667903 A CN 111667903A CN 202010331281 A CN202010331281 A CN 202010331281A CN 111667903 A CN111667903 A CN 111667903A
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- 238000012545 processing Methods 0.000 claims abstract description 14
- 238000004458 analytical method Methods 0.000 claims abstract description 9
- 230000003902 lesion Effects 0.000 claims description 15
- 238000001514 detection method Methods 0.000 claims description 9
- 238000011156 evaluation Methods 0.000 abstract description 5
- 230000000007 visual effect Effects 0.000 abstract description 5
- 238000000034 method Methods 0.000 abstract description 3
- 230000011218 segmentation Effects 0.000 description 6
- 238000002591 computed tomography Methods 0.000 description 2
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- 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
Abstract
The invention provides a medical image processing method and a medical image processing device, wherein the method comprises the following steps: acquiring DICOM format images and Json data of medical images; analyzing the Json data to obtain a focus area in the medical image; acquiring image pixel data from a DICOM format image; respectively combining the image pixel data of the focus area and the image pixel data of the non-focus area to generate a VTI format three-dimensional volume data file; and loading the three-dimensional volume data file in the VTI format. The invention can obtain the characteristics of visual and three-dimensional focuses, thereby assisting doctors to read the films and conveniently and efficiently realizing the analysis of the illness state or the evaluation of the treatment condition.
Description
Technical Field
The present invention relates to the field of image processing technologies, and in particular, to a medical image processing method and a medical image processing apparatus.
Background
Ct (computed tomography), i.e. electronic computed tomography, uses a detector with very high sensitivity to perform cross-section scanning one by one around a certain part of a human body, and has the characteristics of fast scanning time, clear image and the like. Because CT is a tomographic image, a doctor cannot well observe a focus in a three-dimensional state in the process of reading a film, and can only observe the focus on the basis of two-dimensional images layer by layer on an axial position. However, the focus is three-dimensional, and the doctor needs to evaluate the characteristics of the three-dimensional focus, including the size, density, edge, relationship with surrounding tissues, and the like, which cannot be intuitively and accurately realized in a common image reading mode.
In the existing mode, a doctor can only read a focus in a single-level two-dimensional image, or read the focus in three levels based on an MPR (Multi-planar reconstruction) mode, and then perform MIP (maximum Intensity Projection) reading to observe the relation between the focus and surrounding tissues after completing the observation of the focus itself.
Disclosure of Invention
The invention provides a medical image processing method and a medical image processing device for solving the technical problems, and the medical image processing method and the medical image processing device can acquire visual and three-dimensional focus characteristics, so that a doctor is assisted in reading a film, and the analysis of the state of an illness or the evaluation of the treatment condition are conveniently and efficiently realized.
The technical scheme adopted by the invention is as follows:
a medical image processing method, comprising the steps of: acquiring DICOM (digital imaging and Communications in medicine) format images and Json data of medical images; analyzing the Json data to obtain a lesion region in the medical image; acquiring image pixel data from the DICOM-format image; combining the Image pixel data of the focus area and the Image pixel data of the non-focus area respectively to generate a three-dimensional volume data file in a VTI (VTK XML Image data) format; and loading and displaying the three-dimensional volume data file in the VTI format.
The medical image is a CT image.
And analyzing a set of two-dimensional rectangular detection frames and a set of two-dimensional contour point sets in the Json data to obtain a focus area in the medical image.
Combining the image pixel data of the focus area and the image pixel data of the non-focus area respectively to generate a VTI format three-dimensional volume data file, which specifically comprises the following steps: extracting the focus area and the non-focus area from the image pixel data, and combining the focus area and the non-focus area into three-dimensional volume data according to the original coordinates of the focus area and the non-focus area; and applying a Modality LUT to the pixel value of the three-dimensional volume data to obtain a real CT value, and converting the three-dimensional volume data into a VTK data format.
A medical image processing apparatus comprising: the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring DICOM format images and Json data of medical images; an analysis module for analyzing the Json data to obtain a lesion region in the medical image; a second acquisition module for acquiring image pixel data from the DICOM-format image; the generating module is used for respectively combining the image pixel data of the focus area and the image pixel data of the non-focus area to generate a VTI format three-dimensional volume data file; and the loading display module is used for loading and displaying the three-dimensional volume data file in the VTI format.
The medical image is a CT image.
The analysis module is specifically configured to: and analyzing a set of two-dimensional rectangular detection frames and a set of two-dimensional contour point sets in the Json data to obtain a focus area in the medical image.
The generation module is specifically configured to: extracting the focus area and the non-focus area from the image pixel data, and combining the focus area and the non-focus area into three-dimensional volume data according to the original coordinates of the focus area and the non-focus area; and applying a Modality LUT to the pixel value of the three-dimensional volume data to obtain a real CT value, and converting the three-dimensional volume data into a VTK data format.
The invention has the beneficial effects that:
according to the method, the DICOM format image and the Json data are acquired, the Json data are analyzed to obtain the focus area, the image pixel data are acquired from the DICOM format image, the three-dimensional volume data file in the VTI format is generated in a combined mode and is loaded and displayed at the front end, and therefore, the visual and three-dimensional focus characteristics can be acquired in a 3D MIP mode, so that a doctor is assisted in reading, and the analysis of the state of an illness or the evaluation of the treatment condition are conveniently and efficiently achieved.
Drawings
FIG. 1 is a flow chart of a medical image processing method according to an embodiment of the invention;
fig. 2 is a block schematic diagram of a medical image processing apparatus according to an embodiment of 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.
As shown in fig. 1, the medical image processing method of the embodiment of the present invention includes the steps of:
s1, acquiring DICOM format image and Json data of the medical image.
In one embodiment of the invention, the medical image may be a CT image, and the DICOM-formatted image and the Json data of the medical image may be obtained from a database.
S2, the Json data is parsed to obtain a lesion region in the medical image.
For the medical image examination results, the examination program outputs a set of two-dimensional rectangular examination boxes for each nodule, which contains four points ((x1, y1), (x1, y2), (x2, y2), (x2, y1)) representing the position and size of a nodule on a slice CT. Obviously, larger nodes can be simultaneously present on the multi-layer CT, and a two-dimensional rectangular detection frame is given on each layer CT, so that a set of two-dimensional rectangular detection frames is formed and written into Json.
For the segmentation result of the medical image, for each nodule, the segmentation program outputs a set of two-dimensional contour point sets, and on each layer of CT, the segmentation program outputs a set of contour point sets which are connected in sequence to form the contour of the nodule.
Therefore, the focus area in the medical image can be obtained by analyzing the set of two-dimensional rectangular detection boxes and the set of two-dimensional contour point sets in the Json data.
S3, image pixel data is acquired from the DICOM-format image.
S4, image pixel data of the lesion area and the non-lesion area are combined to generate a VTI format three-dimensional volume data file.
The VTI format is a three-dimensional data format output by VTK software, has XML grammar embedded with binary data, has higher flexibility, and can represent a plurality of scalar/vector/tensor data in the same file.
Specifically, the focal region and the non-focal region may be extracted from the image pixel data, and combined into a three-dimensional volume data according to the original coordinates of the focal region and the non-focal region, and then the real CT value is obtained by applying a modiity LUT to the pixel value of the three-dimensional volume data, and the three-dimensional volume data is converted into a VTK data format.
And S5, loading the three-dimensional volume data file in the VTI format.
The three-dimensional volume data in the VTI format can be generated into a disk file and loaded and displayed by the front end of the computer, so that a doctor can directly observe the size, density, edge and other characteristics of a focus and the relationship between the focus and surrounding tissues and the like at the front end of the computer.
In one embodiment of the invention, in order to support MIP reconstruction and further show color information of the physical interior, the VTK tool vtkXMLImageDataWriter of the VTK can be used to write the three-dimensional volume data into a VTI file, which is provided to the front end for showing. Further, the model is rendered via canvas according to the VTI format three-dimensional volume data file, and a camera controller is added so that a user can manually control the orientation and distance of the model.
According to the medical image processing method provided by the embodiment of the invention, the DICOM format image and the Json data are acquired, the Json data are analyzed to obtain the focus area, the image pixel data are acquired from the DICOM format image, and the VTI format three-dimensional volume data file is generated in a combined mode and is loaded and displayed by the front end, so that the visual and three-dimensional focus characteristics can be acquired in a 3D MIP mode, a doctor is assisted in reading, and the analysis of the state of an illness or the evaluation of the treatment condition can be conveniently and efficiently realized.
In order to implement the medical image processing method of the above embodiment, the invention further provides a medical image processing device.
As shown in fig. 2, the medical image processing apparatus according to the embodiment of the present invention includes a first acquiring module 10, a parsing module 20, a second acquiring module 30, a generating module 40, and a loading display module 50. The first acquiring module 10 is configured to acquire DICOM-format images and Json data of medical images; the analysis module 20 is used for analyzing the Json data to obtain a focus area in the medical image; the second obtaining module 30 is used for obtaining image pixel data from the DICOM format image; the generating module 40 is configured to combine image pixel data of a focal region and image pixel data of a non-focal region, and generate a VTI format three-dimensional volume data file; the loading display module 50 is used for loading and displaying a three-dimensional volume data file in a VTI format.
In one embodiment of the present invention, the medical image may be a CT image, and the first obtaining module 10 may obtain a DICOM-format image and Json data of the medical image from a database.
For the medical image examination results, the examination program outputs a set of two-dimensional rectangular examination boxes for each nodule, which contains four points ((x1, y1), (x1, y2), (x2, y2), (x2, y1)) representing the position and size of a nodule on a slice CT. Obviously, larger nodes can be simultaneously present on the multi-layer CT, and a two-dimensional rectangular detection frame is given on each layer CT, so that a set of two-dimensional rectangular detection frames is formed and written into Json.
For the segmentation result of the medical image, for each nodule, the segmentation program outputs a set of two-dimensional contour point sets, and on each layer of CT, the segmentation program outputs a set of contour point sets which are connected in sequence to form the contour of the nodule.
Thus, the parsing module 20 may obtain the lesion region in the medical image by parsing out a set of two-dimensional rectangular check-out boxes and a set of two-dimensional contour point sets in the Json data.
The VTI format is a three-dimensional data format output by VTK software, has XML grammar embedded with binary data, has higher flexibility, and can represent a plurality of scalar/vector/tensor data in the same file.
The generating module 40 may specifically extract a lesion region and a non-lesion region from the image pixel data, combine the lesion region and the non-lesion region into a three-dimensional volume data according to the original coordinates of the lesion region and the non-lesion region, then apply a modility LUT to the pixel values of the three-dimensional volume data to obtain a true CT value, and convert the three-dimensional volume data into a VTK data format.
The three-dimensional volume data in the VTI format can be generated into a disk file and loaded and displayed by the front end of the computer, so that a doctor can directly observe the size, density, edge and other characteristics of a focus and the relationship between the focus and surrounding tissues and the like at the front end of the computer.
In one embodiment of the present invention, in order to support MIP reconstruction and further display color information of the physical interior, the generation module 40 may write the three-dimensional volume data into a VTI file using VTK's tool vtkXMLImageDataWriter, and provide the VTI file to the front-end loading display module 50 for display. Further, the loading display module 50 may render the model according to the VTI format three-dimensional volume data file via canvas, and add a camera controller so that the user can manually control the orientation and distance of the model.
According to the medical image processing device provided by the embodiment of the invention, the DICOM format image and the Json data are acquired, the Json data are analyzed to obtain the focus area, the image pixel data are acquired from the DICOM format image, and the VTI format three-dimensional volume data file is generated in a combined mode and is loaded and displayed by the front end, so that the visual and three-dimensional focus characteristics can be acquired in a 3D MIP mode, a doctor is assisted in reading, and the analysis of the state of an illness or the evaluation of the treatment condition can be conveniently and efficiently realized.
In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implying any number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. The meaning of "plurality" is two or more unless specifically limited otherwise.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (8)
1. A medical image processing method, characterized by comprising the steps of:
acquiring DICOM format images and Json data of medical images;
analyzing the Json data to obtain a lesion region in the medical image;
acquiring image pixel data from the DICOM-format image;
combining the image pixel data of the focus area and the image pixel data of the non-focus area respectively to generate a VTI format three-dimensional volume data file;
and loading and displaying the three-dimensional volume data file in the VTI format.
2. A medical image processing method according to claim 1, wherein the medical image is a CT image.
3. The medical image processing method according to claim 2, wherein the lesion region in the medical image is obtained by analyzing a set of two-dimensional rectangular detection boxes and a set of two-dimensional contour point sets in the Json data.
4. The medical image processing method according to claim 3, wherein the generating of the VTI format three-dimensional volume data file by combining the image pixel data of the focal region and the non-focal region respectively comprises:
extracting the focus area and the non-focus area from the image pixel data, and combining the focus area and the non-focus area into three-dimensional volume data according to the original coordinates of the focus area and the non-focus area;
and applying a Modality LUT to the pixel value of the three-dimensional volume data to obtain a real CT value, and converting the three-dimensional volume data into a VTK data format.
5. A medical image processing apparatus, characterized by comprising:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring DICOM format images and Json data of medical images;
an analysis module for analyzing the Json data to obtain a lesion region in the medical image;
a second acquisition module for acquiring image pixel data from the DICOM-format image;
the generating module is used for respectively combining the image pixel data of the focus area and the image pixel data of the non-focus area to generate a VTI format three-dimensional volume data file;
and the loading display module is used for loading and displaying the three-dimensional volume data file in the VTI format.
6. A medical image processing apparatus according to claim 5, wherein the medical image is a CT image.
7. The medical image processing apparatus according to claim 6, wherein the parsing module is specifically configured to:
and analyzing a set of two-dimensional rectangular detection frames and a set of two-dimensional contour point sets in the Json data to obtain a focus area in the medical image.
8. The medical image processing apparatus according to claim 7, wherein the generating module is specifically configured to:
extracting the focus area and the non-focus area from the image pixel data, and combining the focus area and the non-focus area into three-dimensional volume data according to the original coordinates of the focus area and the non-focus area;
and applying a Modality LUT to the pixel value of the three-dimensional volume data to obtain a real CT value, and converting the three-dimensional volume data into a VTK data format.
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- 2020-04-24 CN CN202010331281.4A patent/CN111667903A/en active Pending
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| CN107507184A (en) * | 2017-09-26 | 2017-12-22 | 上海辉明软件有限公司 | Method for building up, device and the electronic equipment of focus model |
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