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Abdominal muscle labeling method and a labeling device based on a plurality of sub-region templates

A sub-region, abdomen technology, applied in the field of medical image annotation, to ensure accuracy and reduce the burden of daily work

Active Publication Date: 2019-03-22
ZHONGSHAN HOSPITAL FUDAN UNIV +1
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Problems solved by technology

However, regarding a standard abdominal muscle annotation database, a shape template library is generated for each sub-region according to the constructed annotation database. Based on the above-mentioned annotation database and shape template library, each sub-region of the abdominal muscles is separately Carry out automatic segmentation and labeling, which greatly reduces the daily work burden of doctors; at the same time, there is currently no relevant abdominal muscle labeling method and labeling device based on multiple sub-region templates to ensure the accuracy of medical data labeling through result viewing and correction steps. to report

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  • Abdominal muscle labeling method and a labeling device based on a plurality of sub-region templates
  • Abdominal muscle labeling method and a labeling device based on a plurality of sub-region templates
  • Abdominal muscle labeling method and a labeling device based on a plurality of sub-region templates

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Embodiment Construction

[0032] The specific embodiments provided by the present invention will be described in detail below in conjunction with the accompanying drawings.

[0033] Such as figure 1 as shown, figure 1It is a flow chart of the abdominal muscle labeling method based on multiple sub-region templates in the present invention, and mainly includes the following steps:

[0034] S1. Construct a standard abdominal muscle annotation database; the specific steps are: collect the abdominal CT image data of N individuals, select the CT slice image of the middle part of the third lumbar vertebra in each CT image data, and according to the shape characteristics and anatomy of the abdominal muscles Features, define 4 sub-regions of abdominal muscles, mark the above 4 sub-regions on the CT slice image, construct a standard abdominal muscle annotation database, and the annotation database includes three types of information: CT image data, marked area template And the corresponding area number r, wher...

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Abstract

The invention relates to an abdominal muscle labeling method and a labeling device based on a plurality of sub-region templates. According to the characteristics of wide abdominal muscle area, large shape change and diversity, the abdominal muscle is divided into four sub-regions according to the shape characteristics and anatomical significance of the abdominal muscle. Collect standard annotationdata to construct standard abdominal muscle annotation database. At the same time, according to the standard annotation database, according to the four sub-regions of abdominal muscle, multiple shapetemplates of each sub-region are constructed to form shape template library. Based on the annotation database and shape template database, the four sub-regions of abdominal muscle are automatically segmented and annotated by multi-template matching method. At the same time, the marking method and the marking device of the invention can view and revise the result, and refine and revise the markingresult. The automatic labeling method of the invention greatly reduces the daily work burden of the doctor and ensures the accuracy of the medical data labeling.

Description

technical field [0001] The invention relates to the technical field of medical image labeling, in particular to a method and device for labeling abdominal muscles based on multiple sub-region templates. Background technique [0002] The muscle state of the third lumbar vertebrae in the abdomen is an important indicator to measure the nutritional status of a person. Abdominal CT examination is the main means to obtain images of abdominal muscles and then analyze their nutritional status. During the examination, it is necessary to mark the muscle area of ​​the third lumbar vertebrae in the CT image, and then calculate the relevant parameters to judge the nutritional status. At present, the conventional method is that the doctor manually marks the area. Although conventional methods can obtain precise muscle regions, they bring a greater burden to doctors in their daily work. [0003] In recent years, computer-aided methods have been gradually applied to the field of medical ...

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Application Information

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IPC IPC(8): G06T7/00G06T7/11G16H30/40
CPCG06T7/0012G06T7/11G16H30/40G06T2207/10081G06T2207/30004Y02P90/30
Inventor 周继刘迎迎陈世耀刘雷
Owner ZHONGSHAN HOSPITAL FUDAN UNIV
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