Multi-modal medical image fusion method and system based on deep learning

Abstract

The invention provides a multi-modal medical image fusion method and system based on deep learning. The method comprises the following steps: acquiring two-dimensional medical images of at least two modals of a patient; inputting the two-dimensional medical images of the at least two modalities into a pre-trained corresponding image segmentation network model so as to respectively obtain the output of the two-dimensional medical image of each modal body position area; based on a point cloud registration algorithm, performing point cloud registration fusion on the two-dimensional medical image of each modal body position area to obtain a multi-modal fused two-dimensional medical image; and processing the multi-modal fused two-dimensional medical image to obtain a multi-modal fused three-dimensional medical image. The multi-modal medical image registration precision is high, the invention is suitable for various complex image fusion conditions, the operation accuracy of an operator can be improved, and the operation efficiency can be improved.

Description

technical field [0001] The invention relates to the technical field of medical image processing, in particular to a deep learning-based multimodal medical image fusion method and system. Background technique [0002] In the process of modern digital medical diagnosis, medical staff usually need to use the collected multi-modal 3D images of the patient to analyze the patient's lesion before performing the operation, so as to formulate an appropriate operation plan. Since the highlighted image features of each image are different, in order to facilitate the doctor to observe and formulate the operation plan, it is necessary to synthesize the advantages of the images of various modalities collected before the operation, that is, to perform multi-modality image registration to integrate different The images of the modalities are registered to the same angle and the image features of the patient's lesion that can be provided by each image are fused into one image for display. ...

AI Technical Summary

Problems solved by technology

[0005] The present invention provides a multi-modal medical image fusion method and system based on deep learning, which is used to overcome the low accuracy, high complexity, high time cost and ineffective application of multi-modal image registration and fusion in the prior art. Defects such as registration conditions can improve the accuracy of multi-modal image fusion and reduce time costs. It is suitable for a variety of complex image fusion situations, and can also improve the surgical accuracy and efficiency of the surgeon, and can be effectively applied to Effects of non-rigid registration cases

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