Multispectral-based fundus image registration method and system

Abstract

The invention provides a multispectral-based fundus image registration method, comprising the steps: acquiring the multispectral fundus image through RHA, and selecting a template fundus image and a fundus image to be registered; constructing a regression network for obtaining a deformation field between the template fundus image and the fundus image to be registered, and adding a feature balancelayer and a pyramid structure into the regression network; constructing a loss function, wherein the loss function comprises similarity loss of the blood vessel label graph and flattening constraint of a deformation field; and training the network in a weak supervision mode, and taking the processed segmentation image of the fundus image as a label of the training network. According to the multispectral-based fundus image registration method, the registration model is trained by taking the segmentation image as guidance and adopting a weak supervision mode, and practice proves that the methodcan effectively solve the problem of multispectral fundus image registration, and a good effect can be achieved, and the weak supervision segmentation oriented registration method can be expanded to more multimodal image registration problems.

Description

technical field [0001] The present disclosure belongs to the field of image registration, and in particular relates to a multispectral-based fundus image registration method and system. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art. [0003] Medical image registration is a basic task in medical image processing and a hotspot in medical image processing at present, which has very important significance in clinical diagnosis and disease treatment. Medical image registration is to find an ideal spatial transformation between two images, so that the corresponding points of the two images achieve a complete match in terms of spatial and anatomical positions, or at least all clinical diagnosis concerns are matched. [0004] The multi-spectral fundus image is a special fundus imaging, which uses different monochromatic LED light sources to project into...

AI Technical Summary

Problems solved by technology

The second difficulty is that the movement of the eyeball causes the deformation of the fundus

However, in fact, obtaining accurate segmentation information is very expensive, requiring corresponding experts to spend a lot of energy on labeling

The second is a learning-based registration method, which requires pre-aligned image pairs to train a multimodal registration network, but it is difficult to obtain precisely aligned image pairs.

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