Abdominal wall muscle segmentation method based on image data and system thereof

Abstract

The invention is suitable for the field of image processing technology, and provides an abdominal wall muscle segmentation method based on image data and a system thereof. The method comprises the steps of A, performing adaptive bilateral filtering processing on the acquired image data of the abdominal wall muscle image; B, according to the image characteristic of the abdominal hernia muscle imagecharacteristic, setting a pre-segmenting abdominal hernia muscle image area of the of the pre-processed abdominal wall muscle, and extracting an initial abdominal hernia muscle segmenting area; C, setting an image characteristic function of the abdominal hernia muscle, and extracting an abdominal hernia muscle edge contour in the initial abdominal hernia muscle segmenting area; and performing optimization processing on the abdominal hernia muscle edge contour, thereby obtaining the final abdominal hernia muscle segmenting area. Therefore the method and the system realize automatic extractionand segmentation of the image area of the abdominal hernia muscle, and three-dimensional multi-angle visual imaging of the abdominal hernia muscle area.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to a method and system for segmenting abdominal wall muscles based on image data. Background technique [0002] In modern medical care, B-ultrasound, CT (Computed Tomography) and MRI (Nuclear Magnetic Resonance Imaging, nuclear magnetic resonance imaging) are common imaging diagnostic techniques for diagnosing abdominal wall hernia disease. During clinical application, B Ultrasound, CT and MRI imaging have the following three shortcomings in the diagnosis of abdominal wall hernia disease: [0003] B-ultrasound, CT and MRI images are not clear about the identification of abdominal wall muscles in abdominal wall hernia defect. Most of the patients with abdominal wall hernia will have lesions of the abdominal wall muscles around the defect, and the CT value of this part of the tissue will decrease (the CT value of normal skeletal muscle is 45-75, but the CT value of t...

AI Technical Summary

Problems solved by technology

B-ultrasound or abdominal CT plain scan to show the location and size of the hernia ring defect (small: 0-4cm, medium: 4-8cm, large: 8-12cm, giant: >12cm), but the two-dimensional image cannot consider the abdominal wall hernia Comprehensive situation (area of ​​hernia ring, volume of hernia sac), not to mention the lesions of the abdominal wall muscles around the defect

[0006] In summary, the existing technology obviously has inconvenience and defects in actual use, so it is necessary to improve it.

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