Cross-modal medical image registration method and device

Abstract

The invention discloses a cross-modal medical image registration method. The method comprises the following steps: providing a training set comprising a floating image of a first modal and a referenceimage of a second modal; inputting the floating image into an image conversion network, and converting the floating image into a conversion image of a second modal; inputting the floating image and the reference image into a cross-modal flow sub-network to output a first deformation field; inputting the converted image and the reference image into the single-mode flow sub-network to output a second deformation field; inputting the first deformation field and the second deformation field into a deformation field fusion network to output a final deformation field; inputting the floating image and the final deformation field into a space transformation network to obtain a floating image after distortion transformation of the final deformation field; obtaining a first total loss function according to the transformed floating image and the reference image, and performing supervised training on the network by taking minimization of the first total loss function as a target; and inputting ato-be-registered image into the trained network to obtain a registered image. The cross-modal medical image registration method can greatly improve the cross-modal medical image registration effect.

Description

technical field [0001] The invention relates to the technical field of medical image registration, in particular to a cross-modal medical image registration method and device. Background technique [0002] Medical image registration is an optimization process that aligns a floating image with a reference image based on the appearance of a medical image, with the goal of finding the best spatial transformation that aligns regions of interest in input images. As a key technology of image-guided therapy, medical image registration attempts to establish anatomical correspondence between different medical images, and is applied to many clinical scenarios such as endoscopy, disease diagnosis, surgical guidance, and radiotherapy. Medical image registration is a broad research topic. According to the type of image to be registered, it can be divided into single-modal registration and cross-modal registration. According to the type of registration transformation, it can be divided in...

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Problems solved by technology

[0013] However, the above-mentioned cross-modal image registration technology and M2U registration technology based on VoxelMorph+MIND usually cannot achieve satisfactory registration results.

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