Intravascular ultrasound image three-dimensional reconstruction method and system based on deep learning

Abstract

The invention discloses an intravascular ultrasound image three-dimensional reconstruction method and a system based on deep learning, and the method comprises the steps: collecting a bifurcated bloodvessel image and a normal blood vessel image in an IVUS image, carrying out the labeling, and making a first data set; classifying the first data set by using a classification network to obtain a bifurcated blood vessel image and a normal blood vessel image; respectively marking the inner and outer membranes of the bifurcated blood vessel image and the inner and outer membranes of the normal blood vessel image to form a second data set and a third data set; respectively segmenting the second data set and the third data set by utilizing a semantic segmentation network to respectively obtain inner and outer membrane images of the bifurcated blood vessel and the normal blood vessel; and performing three-dimensional reconstruction on the obtained inner and outer membrane images of the bifurcated blood vessel and the normal blood vessel. According to the method, bifurcated blood vessels and normal blood vessels are classified by using a deep learning method, so that the speed and accuracyof three-dimensional reconstruction can be improved, the reconstruction result is more accurate, intuitive judgment of doctors is facilitated, and the method is of great significance to auxiliary diagnosis of diseases.

Description

technical field [0001] The invention belongs to the technical field of medical detection, and in particular relates to a method and system for three-dimensional reconstruction of intravascular ultrasound images based on deep learning. Background technique [0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art. [0003] In recent years, more and more researchers have begun to pay attention to processing techniques such as pattern recognition, classification and segmentation in medical image processing. Machine learning techniques enable researchers to develop and utilize complex models to classify or predict various abnormalities or diseases or to identify and segment medical lesions. Deep learning is a new field of machine learning research, and its motivation lies in the establishment and simulation of the human brain to analyze and study neural networks and simulate the hum...

AI Technical Summary

Problems solved by technology

[0005] However, due to the existence of vascular bifurcations in blood vessels, the existence of bifurcated blood vessels has caused great difficulties in the segmentation and reconstruction of intima and intima.

The methods for three-dimensional reconstruction of intravascular images involved in the prior art all take into account the influence of vessel bifurcations on the reconstruction results

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