Two-dimensional and three-dimensional medical image registration method and system based on deep learning

Abstract

The invention discloses a two-dimensional and three-dimensional medical image registration method and system based on deep learning, and the method comprises the steps: segmenting a target focus in athree-dimensional medical image through deep learning, and then reconstructing a segmented image; obtaining edge information of the focus from the reconstructed three-dimensional image according to the clinical prior information to obtain a plurality of binary images; obtaining a part needing to be observed by a doctor through a camera, and calculating the edge of the target focus through deep learning to obtain another binary image; registering the two types of binary images by using an image registration technology so as to obtain a transformation matrix between the two types of images, andapplying the transformation matrix to the original image, so that the image registration problem is solved. By means of the method, a doctor can have a pair of real-time perspective eyes in the diagnosis and treatment process, the medical image registration task is better completed, imaging examination information of a patient is more fully utilized, and clinical treatment is assisted.

Description

technical field [0001] The invention belongs to the field of medical image registration, mainly applies deep learning technology, and integrates clinical prior knowledge to perform multi-modal and multi-dimensional medical image registration. Background technique [0002] In the medical field, medical imaging examinations can provide imaging information of internal lesions in the body, such as the shape, size, capsule, and blood supply of lesions. By reading the films, doctors integrate the information provided by imaging studies with their own knowledge, so as to diagnose and treat patients (such as surgery). In the process of surgery or treatment, doctors cannot see deep information through superficial tissues, and can only use a layer-by-layer approach to approach the lesion. This process requires doctors to have solid theoretical literacy and surgical experience. If the imaging pictures containing the three-dimensional information of the patient's lesion can be processe...

AI Technical Summary

Problems solved by technology

However, the existing work has the following deficiencies: 1. The clinical prior information is not fully utilized; 2. The clinical work is not fully integrated.

However, in the above-mentioned patents, the registration accuracy is not high, and the image containing the three-dimensional information of the lesion cannot be projected onto the two-dimensional image or the projection effect is not good. Unlike the above-mentioned invention or existing similar inventions, the present invention uses deep learning technology Extract image features, use clinical prior knowledge to reduce the amount of calculation, and disclose a method for registration of medical 3D images and 2D images

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