Segmentation method and segmentation system for large joint tissue

Abstract

The invention provides a segmentation method and a segmentation system for large joint tissue, solving the technical problem of low segmentation efficiency of the existing joint tissue. The segmentation method comprises the steps: forming an image segmentation reference; forming tissue types and position features of a single pixel in the MRI image according to the image segmentation reference so as to determine a tissue plane contour; and forming a tissue three-dimensional contour according to the tissue plane contour in each MRI image in combination with the image segmentation reference. Thetissue segmentation process is simplified by utilizing skeleton features; related image and information characteristics are used to form automatic processing of an object contour and identification accuracy is increased; and an image quantization rule is formed by using a segmentation reference, and pixel connotation information and a modeling framework are effectively fused, so that a large jointcomposition tissue can realize automatic main body segmentation, accurate contour positioning and automatic three-dimensional modeling in an MRI image, and the identification efficiency of professional human identification resources is effectively improved.

Description

technical field

[0001] The invention relates to the technical field of medical image processing, in particular to a large joint tissue segmentation method and segmentation system. Background technique

[0002] The composition of joints is complex. Taking the wrist joint as an example, it includes bones, tendons, vessels, and nerves. The contours of tissues other than bones are often unclear due to the gray resolution of MRI (Magnetic Resonance Imaging, MRI). The combination of edge gray areas between tissues leads to difficulties in image segmentation between tissues.

[0003] In the prior art, it is necessary to manually perform selective editing, defect compensation processing, artifacts and redundant data separation on various tissue patterns, and then use the region growing method to generate segmentation results to establish a complete digital model, such as large Contour segmentation of bone tissue. This will consume a lot of time for operators, and professional reso...

Examples

Embodiment Construction

[0053] In order to make the purpose, technical solution and advantages of the present invention clearer and clearer, the present invention will be further described below in conjunction with the accompanying drawings and specific embodiments. Apparently, the described embodiments are only some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0054] The segmentation method of large joint tissue in one embodiment of the present invention is as follows: figure 1 shown. exist figure 1 , this example includes:

[0055] Step 100: Form an image segmentation benchmark.

[0056]Those skilled in the art can understand that a set of image references of parallel sections includes but not limited to a plane coordinate reference within an image, a coordinate transfo...

technical field

[0001] The invention relates to the technical field of medical image processing, in particular to a large joint tissue segmentation method and segmentation system. Background technique

[0002] The composition of joints is complex. Taking the wrist joint as an example, it includes bones, tendons, vessels, and nerves. The contours of tissues other than bones are often unclear due to the gray resolution of MRI (Magnetic Resonance Imaging, MRI). The combination of edge gray areas between tissues leads to difficulties in image segmentation between tissues.

[0003] In the prior art, it is necessary to manually perform selective editing, defect compensation processing, artifacts and redundant data separation on various tissue patterns, and then use the region growing method to generate segmentation results to establish a complete digital model, such as large Contour segmentation of bone tissue. This will consume a lot of time for operators, and professional reso...

Examples

Embodiment Construction

[0053] In order to make the purpose, technical solution and advantages of the present invention clearer and clearer, the present invention will be further described below in conjunction with the accompanying drawings and specific embodiments. Apparently, the described embodiments are only some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0054] The segmentation method of large joint tissue in one embodiment of the present invention is as follows: figure 1 shown. exist figure 1 , this example includes:

[0055] Step 100: Form an image segmentation benchmark.

[0056]Those skilled in the art can understand that a set of image references of parallel sections includes but not limited to a plane coordinate reference within an image, a coordinate transfo...

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