Label-free pancreatic image automatic segmentation system based on adversarial learning

Abstract

The invention discloses a label-free pancreatic image automatic segmentation system based on adversarial learning, and the system employs an adversarial learning method to search label image data and common image features in label-free image data, and strengthens the personalized image features of the label-free image data, and a pancreas image segmentation model suitable for the label-free pancreas CT image is constructed; a Transform structure is introduced to segment a pancreas CT image, pixel block partition processing is performed on pancreas CT image data, a self-attention mechanism is added to establish a long-connection cross-correlation relation between pixel blocks, a residual structure is used in a multi-stage encoder-decoder structure, multi-scale pancreas target image features can be subjected to weighted interaction, and the segmentation effect on small targets such as pancreatic tissues is obviously improved. According to the method, a reliable segmentation result can be given for label-free pancreas CT image data, the film reading time of a doctor is effectively shortened, the diagnosis and treatment process of pancreas-related diseases is optimized, and the diagnosis and treatment efficiency of the doctor is improved.

Description

technical field [0001] The invention belongs to the technical field of image data processing, and in particular relates to an automatic segmentation system of unlabeled pancreas images based on adversarial learning. Background technique [0002] Pancreas-related diseases develop rapidly clinically and have poor prognosis. Pancreatic cancer is a highly malignant digestive tract tumor with a 5-year survival rate of less than 5%. Early detection of pancreatic lesions and precise treatment are crucial to improving the quality of life of patients with pancreatic-related diseases. Pancreatic cancer treatment options currently mainly include surgical resection and neoadjuvant therapy, both of which require precise positioning of pancreatic tissue before surgery. Abdominal computed tomography (Computed Tomography) is an important examination method in the diagnosis process of pancreas-related diseases. The automatic segmentation tool of pancreatic CT images can assist radiologists ...

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to provide an automatic segmentation system for unlabeled pancreatic images based on adversarial learning to solve the following technical problems:

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