Image registration method and related model training method, equipment and device

Abstract

The application discloses an image registration method and a related model training method, equipment and device. The method includes: obtaining a real two-dimensional image and a reference two-dimensional image, and using a virtual image feature extraction network of an image registration model to perform feature extraction on the reference two-dimensional image to obtain a first virtual feature map; wherein, the image registration model has been used The virtual image is pre-trained, and the virtual image feature extraction network participates in the pre-training. The virtual image is generated based on the virtual target; the real image feature extraction network of the image registration model is used to extract the feature of the real two-dimensional image to obtain the first real feature Figure; where the real image feature extraction network does not participate in pre-training; use the difference between the first real feature map and the first virtual feature map to adjust the network parameters of the real image feature extraction network. Through the method, the training effect of the image registration model is improved and the training cost is reduced.

Description

technical field [0001] The present application relates to the technical field of image processing, in particular to an image registration method and related model training methods, equipment, and devices. Background technique [0002] Image registration is the process of matching two or more images acquired at different times, different sensors (imaging devices) or under different conditions (camera position and angle, etc.). Medical image registration refers to seeking a kind of (or a series of) spatial transformations for a medical image to make it consistent with the corresponding points on another medical image. [0003] Using neural networks to register images shows great potential and has a wide range of applications. At present, the neural network model samples trained for registration are real images that have been manually registered, but because manual registration of real images takes a long time and is limited by imaging conditions in real environments, it can b...

AI Technical Summary

Problems solved by technology

At present, the neural network model samples trained for registration are real images that have been manually registered, but because manual registration of real images takes a long time and is limited by imaging conditions in real environments, it can be used for There are few sample images for training, and the price is high, which leads to certain restrictions on the application of neural network models trained with real images

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