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Method, device and system for identifying and segmenting lymph node area of nasopharynx cancer

A technology for lymph nodes and nasopharyngeal cancer, applied in the field of identification and segmentation of lymph node regions of nasopharyngeal cancer, can solve the problems of complicated steps, no lymph node design model, non-end-to-end and other problems, and achieve the effect of improving accuracy

Active Publication Date: 2022-05-06
SUN YAT SEN UNIV CANCER CENT
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, the existing technologies still have the following defects: the steps of these methods are cumbersome, the structure is not end-to-end, and a reasonable model is not fully designed according to the morphological characteristics of lymph nodes

Method used

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  • Method, device and system for identifying and segmenting lymph node area of nasopharynx cancer
  • Method, device and system for identifying and segmenting lymph node area of nasopharynx cancer
  • Method, device and system for identifying and segmenting lymph node area of nasopharynx cancer

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specific Embodiment 1

[0025] The embodiment of the present invention firstly describes a method for identifying and segmenting lymph node regions of nasopharyngeal carcinoma. figure 1 A flow chart of an embodiment of a method for identifying and segmenting lymph node regions of nasopharyngeal carcinoma according to the present invention is shown.

[0026] Such as figure 1 As shown, the method includes the following steps:

[0027] S1: Acquire the magnetic resonance image of the segmentation to be identified.

[0028] S2: Identify and segment the magnetic resonance image by using a preset lymph node identification and segmentation model, so as to obtain a segmented region image.

[0029] The lymphatic recognition segmentation model is an end-to-end, coarse-to-fine, three-dimensional deep-supervised convolutional neural network three-dimensional model. In order to improve the accuracy of the identification and segmentation of the lymph node region of nasopharyngeal carcinoma, the embodiment of the...

specific Embodiment 2

[0047] Furthermore, the embodiment of the present invention also describes a method for identifying and segmenting lymph node regions of nasopharyngeal carcinoma. figure 2 A flow chart of another embodiment of a method for identifying and segmenting lymph node regions of nasopharyngeal carcinoma according to the present invention is shown.

[0048] Such as figure 2 As shown, the method includes the following steps:

[0049] A1: Obtain a preset first training image data set and a preset model to be trained.

[0050] The model to be trained is an end-to-end, coarse-to-fine, three-dimensional deep-supervised convolutional neural network three-dimensional model. Wherein, the first training image data set includes nasopharyngeal carcinoma magnetic resonance image data collected from a hospital or a medical center.

[0051] In one embodiment, the model to be trained includes an input module, an encoding module, a decoding module, and an output module; wherein, the input module ...

specific Embodiment 3

[0064] In addition to the above method, the embodiment of the present invention also describes a device for identifying and segmenting lymph node regions of nasopharyngeal carcinoma. image 3 A structural diagram of an embodiment of an apparatus for identifying and segmenting lymph node regions of nasopharyngeal carcinoma according to the present invention is shown.

[0065] Such as image 3 As shown, the identification and segmentation device includes a data acquisition unit 11 and an identification and segmentation unit 12 .

[0066] Wherein, the data acquisition unit 11 is used to acquire the magnetic resonance image of the segmentation to be identified.

[0067] The identification and segmentation unit 12 is used to identify and segment the nasopharyngeal carcinoma lymph nodes through the preset lymph node identification and segmentation model, so as to obtain the image of the segmented region; the lymph node identification and segmentation model is an end-to-end three-di...

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Abstract

The invention discloses a nasopharynx cancer lymph node area identification and segmentation method, device and system. The device comprises a data acquisition unit and an identification and segmentation unit. The system comprises an identification segmentation module and a data storage module. A magnetic resonance image to be identified and segmented is identified and segmented through an end-to-end coarse-to-fine three-dimensional deep supervised convolutional neural network three-dimensional model, so that a segmented region including a nasopharyngeal carcinoma lymph node is obtained, and the identification and segmentation method, device and system improve the accuracy of identification and segmentation of the nasopharyngeal carcinoma lymph node region; furthermore, according to the nasopharynx cancer lymph node area identification and segmentation method, device and system provided by the invention, the first training image data set is processed through a preset double-auditing data processing method to obtain the second training image data set, so that a reasonable model is designed fully according to the morphological characteristics of the lymph node, and the accuracy of identification and segmentation of the nasopharynx cancer lymph node area is improved. And the accuracy of identification and segmentation of the nasopharynx cancer lymph node region is improved.

Description

technical field [0001] The invention relates to the field of identification and segmentation of lymph node regions of nasopharyngeal carcinoma, and relates to a method, device and system for identification and segmentation of lymph node regions of nasopharyngeal carcinoma. Background technique [0002] Among newly diagnosed patients with nasopharyngeal carcinoma, metastatic lymph nodes are detected in approximately 70%-80% of cases at the time of first diagnosis. Accurate spatial modeling of metastatic lymph nodes is important for successful treatment. Artificial intelligence (AI) has been rapidly developed in the past decade, showing promising performance in the recognition and automatic segmentation of normal anatomical structures or lesions in medical images. Segmentation of regions of interest (ROI) or lesions is labor-intensive, both in imaging studies during radiation therapy and in delineation studies of the gross tumor volume (GTV), so it is necessary to reduce the ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/11G06V20/64G06K9/62G06N3/04G06N3/08G06V10/774G06V10/26G06V10/82
CPCG06T7/11G06N3/08G06T2207/10088G06T2207/20081G06T2207/20084G06T2207/30096G06N3/045G06F18/214
Inventor 李超峰邓一术经秉中陈浩华李彬
Owner SUN YAT SEN UNIV CANCER CENT
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