Deep learning-based multi-level segmentation method for pelvis and artery blood vessels thereof

Abstract

The invention relates to the technical field of pelvis and pelvis artery blood vessel tree segmentation, in particular to a deep learning-based pelvis and pelvis artery blood vessel multi-level segmentation method, which is used for solving the problem that an abdomen pelvis and a pelvis artery blood vessel tree cannot be automatically, efficiently and accurately segmented in a multi-resolution CTimage in the prior art. The method comprises the following steps: step 1, preparing and labeling data; 2, preprocessing the data; 3, constructing a first-level segmentation model of the 3D convolutional neural network based on multi-level segmentation; 4, constructing a second-stage segmentation model; 5, training a first-stage segmentation model and a second-stage segmentation model by using thecalibrated data and the synthesized loss function; and 6, performing abdomen information segmentation on the input three-dimensional CT image by using the first-stage segmentation model and the second-stage segmentation model trained in the step 5. According to the method, the abdominal pelvis and the pelvis vascular tree can be automatically, efficiently and accurately segmented in the multi-resolution CT image.

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

Images