A lung CT and MRI image fusion algorithm

Abstract

The invention belongs to the technical field of medical image processing and computer vision, and particularly relates to a lung CT and MRI image fusion algorithm. According to the method, an image isfused under an inverse problem model, a loss function is constructed under a variational framework, and an optimal solution is obtained by minimizing the loss function. According to the method, the research advantage of the image in a wavelet domain is utilized, the wavelet coefficient is put into a loss function, and non-convex regularization is carried out on the wavelet coefficient to increasethe sparsity of the wavelet coefficient, so that a better image recovery effect is obtained. The convex property of the whole loss function is kept by adjusting parameters, so that a global optimal solution is obtained through convex optimization, and finally, a fusion image is obtained through wavelet inverse transformation. According to the method, the advantages of CT imaging in the aspect oflung texture and the advantages of an MRI imaging sequence in the aspect of lung focus are combined, the information amount of the fusion image is enriched, a doctor can more clearly find the advantage information of the two imaging sensors in lung imaging on the fusion image, and more accurate judgment can be made in a shorter time.

Description

technical field [0001] The invention belongs to the technical field of medical image processing and computer vision, and in particular relates to a lung CT and MRI image fusion algorithm. Background technique [0002] The lung is an important organ that maintains the human respiratory system. Lung disease is one of the important diseases that threaten human life today. Common lung diseases include lung cancer and tuberculosis. Among them, lung cancer is the fastest growing morbidity and mortality rate. It is one of the most serious malignant tumors that threaten health and life. In the past 50 years, many countries have reported that the morbidity and mortality of lung cancer have increased significantly. The incidence and mortality of lung cancer in men rank first among all malignant tumors, and the incidence and mortality of lung cancer occupy the second place in women. For the detection of lung cancer and other diseases, lung CT scans are usually used. CT scans can cover...

AI Technical Summary

Problems solved by technology

The algorithm of medical image fusion also mainly involves the traditional pixel-level image fusion method, including the small improvement of the pixel value selection scheme, that is, without any transformation domain processing on the image, and directly averages the corresponding pixels on each source image. After simple operations such as selection, it is fused into a new image; the image is decomposed into multiple layers in the wavelet domain, the image wavelet pyramid is constructed, and the wavelet coefficients of different layers are processed differently. This method has a great breakthrough in medical image fusion. In some scenes, better results than traditional image fusion algorithms are obtained, but this method also has certain limitations, sometimes resulting in the loss of image details, and being susceptible to noise interference, etc.

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