Multi-mode cooperation esophageal cancer lesion image segmentation system based on self-sampling similarity

Abstract

The invention belongs to the technical field of medical image intelligent processing, and particularly relates to a multi-mode cooperation esophageal cancer lesion image segmentation system based on self-sampling similarity. For early esophageal cancer diagnosis, firstly, a white light image and an NBI data set which are paired are constructed; the segmentation system comprises a feature extraction encoder, a self-sampling similar feature separation module and a feature fusion decoder. the white light image and the NBI are taken as multi-modal input, and features of two modals are extracted respectively by two encoders; for each mode, the self-sampling similar feature separation module effectively distinguishes lesion region features from normal regions; and the decoder completes multi-modal feature fusion in a feature domain, and finally outputs lesion segmentation results of two modal images. Experimental results show that the features of different modes can be reasonably fused, the lesion area and the normal area are remarkably distinguished, accurate segmentation of the lesion area is achieved, and the efficiency of clinical diagnosis is improved.

Description

technical field [0001] The invention belongs to the technical field of medical image intelligent processing, in particular to an esophageal cancer lesion image segmentation system, more specifically, to a self-sampling similarity-based multi-modal cooperative esophageal cancer lesion image segmentation system. Background technique [0002] Esophageal cancer is a common upper gastrointestinal cancer in China and developing countries, ranking sixth in cancer deaths in the world [1] . Studies have shown that the 5-year survival rate of patients with advanced esophageal cancer is less than 20%, but it can exceed 85% in the early stage. Advanced unresectable tumors are the main cause of poor prognosis in most patients with esophageal cancer. Therefore, accurate diagnosis of early esophageal cancer plays an important role in reducing mortality. [0003] Endoscopic screening significantly reduces mortality from esophageal cancer. White-light endoscopic imaging (WH) is the most ...

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Problems solved by technology

[0006] Although the above methods have achieved certain results, the researchers only considered the use of white light images

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