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

A deep learning and medical image technology, applied in image analysis, image enhancement, image data processing, etc., can solve the problems of insufficient integration of clinical work, low registration accuracy, and insufficient use of clinical prior information, etc.

Active Publication Date: 2020-12-29
WUHAN UNIV
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  • Abstract
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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 th...

Method used

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

Examples

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Embodiment 1

[0097] Embodiment 1: A laparoscopic kidney cancer surgery assisting system (1)

[0098] At present, laparoscopic partial nephrectomy is usually used for the treatment of RCC. When resecting a renal tumor, the doctor needs to select the cutting site and cutting thickness by reading the film and combining experience. Too little cutting can result in residual tumor with positive margins; too much cutting can lead to renal hemorrhage with potential impact on renal function. Especially for endogenous renal tumors, there is often a lack of clear markers to guide the surgical site under endoscopy. This clinical problem can be solved based on the embodiment of this patent. As a special case, the imaging data in this embodiment is illustrated by CT data, and the two-dimensional data is illustrated by laparoscopic images during kidney tumor surgery. The overall implementation steps are as follows:

[0099] 1. CT image segmentation network

[0100] The construction of CT image segme...

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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...

Claims

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Application Information

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IPC IPC(8): G06T7/33G06T7/10
CPCG06T7/337G06T7/10G06T2207/10081G06T2207/10088G06T2207/10104G06T2207/20081G06T2207/20084G06T2207/30096
Inventor 王磊杨瑞李彦泽张烨陈志远刘修恒
Owner WUHAN UNIV
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