A multi-level segmentation method of pelvis and its arteries based on deep learning

Abstract

The present invention relates to the technical field of segmentation of pelvis and pelvic artery tree, in particular to a multi-level segmentation method of pelvis and its arterial vessels based on deep learning, which is used to solve the problem of multi-resolution CT in the prior art. The problem of automatic, efficient, and accurate segmentation of the abdominal pelvis and pelvic artery vascular tree in images. The present invention includes step 1: data preparation and labeling; step 2: data preprocessing; step 3: construction of a first-level segmentation model based on a multi-level segmentation 3D convolutional neural network; step 4: construction of a second-level segmentation model; 5: Use the calibrated data and the synthetic loss function to train the first-level segmentation model and the second-level segmentation model; Step 6: Use the first-level segmentation model and the second-level segmentation model trained in step 5 to input 3D CT images Perform abdominal information segmentation. In the present invention, the abdominal pelvis and the pelvic vascular tree can be automatically, efficiently and accurately segmented in multi-resolution CT images.

Description

technical field [0001] The present invention relates to the technical field of segmentation of pelvis and pelvic artery tree, and more specifically relates to a multi-level segmentation method of pelvis and its arterial vessels based on deep learning. Background technique [0002] Lateral lymph node metastasis is an important metastasis pathway of low rectal cancer. Radiotherapy and chemotherapy are not effective for it, which affects the prognosis of rectal cancer patients. As an effective treatment, lateral lymph node dissection, with the popularization of laparoscopic surgery and surgeons The improvement of skills has been more and more widely used in clinical practice, and more and more evidence-based medical evidence shows that lateral lymph node dissection (LLND) can reduce the local recurrence rate of rectal cancer in the pelvis, and the indications for surgery Accurate lateral lymph node dissection can also bring survival benefits. Identification of pelvic lymph node...

AI Technical Summary

Problems solved by technology

[0009] Based on the above problems, the present invention provides a multi-level segmentation method of the pelvis and its arteries based on deep learning, which is used to solve the problem of not being able to automatically, efficiently and accurately segment the abdomen in multi-resolution CT images in the prior art Problems with the pelvis and pelvic arterial tree

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