Endoscopic image segmentation method based on single image and deep learning network

Abstract

An endoscopic image segmentation method based on a single image and a deep learning network achieves real-time and accurate segmentation for a single case, and provides support for making a treatment plan based on an endoscopic image in clinical medicine. The endoscopic image segmentation method first proposes a single image-based training set generation method to automatically generate a training set, and further proposes a lightweight deep learning network EUnet to perform feature fitting on the generated training set, to achieve endoscopic image segmentation and obtain a segmentation result of a lesion region. The endoscopic image segmentation method can significantly improve segmentation accuracy and has advantages of a small volume, high real-time performance, and easy operation. Especially in processing of endoscopic images of rare cases such as a gastric cancer and an esophageal cancer, the endoscopic image segmentation method has significant advantages in accuracy and speed, and has clinical application value.

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