Brain image registration method based on DGAN

Abstract

The existing brain image registration technology has defects in registration precision and speed, and is poor in coping capacity for large deformation in an image to be registered. In order to realize efficient and rapid registration of brain images and facilitate treatment of doctors, the invention provides a brain image registration method (D-GAN) based on a generative adversarial network. A convolutional neural network and denoising and feature enhancement are added in front of the generated model. By adding denoising and feature enhancement, the definition of the image can be higher, and more accurate processing of the image is facilitated. In the generation model, extraction of multi-scale features of data is realized through a U-shaped convolutional network, a discrimination network inputs a sample probability graph obtained by the generation model and a sample truth value label into a deep convolutional network together, a real sample is endowed with a relatively high label, and a generated sample is endowed with a relatively low label. Network parameter weights are adjusted through mutual counterbalance of the generation model and the discrimination model, and the whole network is converged when the generation model and the discrimination model are balanced. According to the invention, the generalization ability of the model can be enhanced by automatically learning the mapping relation between the same data set. According to the invention, accurate and rapid registration can be realized.

Description

technical field [0001] The invention belongs to the technical field of medical image processing, and in particular relates to a method for brain image registration. Background technique [0002] Medical imaging technology provides modern clinical medicine with X-ray imaging, CT computed tomography, US ultrasound imaging, MRI magnetic resonance imaging, FMRI functional magnetic resonance imaging, MRA magnetic resonance angiography, DSA digital subtraction angiography, SPECT single photon emission Tomography imaging, PET positron emission tomography imaging, DF digital decane light contrast imaging and other image information FML with different functions and forms. In clinical diagnosis and treatment, doctors often need to obtain comprehensive and useful information from images obtained in different modalities or in different periods, W for disease diagnosis, treatment and surgical follow-up. Although various imaging technologies have been developed rapidly, and the imaging e...

AI Technical Summary

Problems solved by technology

[0006] In order to solve the problem of misjudgment and missed diagnosis in manual registration in medical image registration, and the timeliness of traditional registration methods is too low, the present invention provides a method for automatically and accurately registering brain images using generative confrontation networks

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