Low-field-intensity MR stomach segmentation method based on transfer learning image enhancement

A transfer learning and image enhancement technology, applied in the field of medical image processing, can solve the problems of many artifacts, low field intensity MR images with large noise, and less image data, etc., to improve the segmentation performance, optimize the convolution structure, and avoid human factors. the effect of interference
CN112102276AActive Publication Date: 2020-12-18XIDIAN UNIV +1
9 Cites 6 Cited by

Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
XIDIAN UNIV
Publication Date
2020-12-18

Smart Images

  • Figure 1
    Figure 1
  • Figure 2
    Figure 2
  • Figure 3
    Figure 3
Patent Text Reader

Abstract

The invention discloses a low-field-intensity MR stomach image segmentation method based on transfer learning image enhancement. The method mainly solves the problems that a low-field-intensity 3DMR image is large in noise, more in artifacts and less in image data. According to the scheme, the method comprises the following steps: acquiring high-field-intensity and low-field-intensity 3DMR stomachimage data sets and corresponding label data sets, and preprocessing the image data; inputting the preprocessed data into a cyclic generative adversarial network to obtain an enhanced pseudo-low field intensity 3DMR stomach image set; constructing and training a 3D Res3Unet segmentation network; and inputting the pseudo low-field-intensity 3DMR stomach image set into a segmentation network, completing fine adjustment of segmentation network parameters, forming a 3D Res3Unet segmentation network after transfer learning, and inputting test data into the network to obtain a segmentation result.According to the method, the segmentation of the low-field-intensity 3DMR stomach image is realized, and the image segmentation precision is effectively improved.
Need to check novelty before this filing date? Find Prior Art

Description

technical field

[0001] The invention belongs to the technical field of medical image processing, and further relates to image segmentation technology, specifically a low-field-strength MR gastric image segmentation method based on transfer learning image enhancement, which can be used to accurately segment the gastric region in low-field-strength 3DMR images. segmentation. Background technique

[0002] At present, the incidence rate of gastric cancer is second only to lung cancer, and the mortality rate ranks third. There are about 1.2 million new cases of gastric cancer every year in the world, and China accounts for about 40% of them. The detection rate of early gastric cancer in my country is low, only about 20%, and most of them have reached the advanced stage when they are discovered, and the overall 5-year survival rate is less than 50%. Therefore, research on the diagnosis of gastric diseases has received extensive attention, and more accurate and efficient medical ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More