Skin disease image lesion segmentation method based on deep convolutional neural network

Abstract

The invention belongs to the field of computer aided diagnosis and medical image processing, and relates to a skin disease image focus segmentation method based on a deep convolutional neural network,which is used for improving the quality of a skin disease image and further improving the focus segmentation accuracy so as to obtain more accurate focus information. The method comprises the specific steps that data preprocessing is responsible for carrying out noise reduction processing on a skin disease image, and removing artificial and natural noise which hinders focus position determinationin the image; the data expansion is responsible for expanding a data set by deforming and rotating the image subjected to the noise reduction processing; a segmentation model is constructed to perform first feature extraction on the image, encoding is performed to obtain more detail features, and the features obtained at the first time are fused to obtain a prediction graph;.

Description

technical field [0001] The invention belongs to the field of computer-aided diagnosis and medical image processing, and in particular relates to a feature extraction and fusion method based on a deep hole convolution network. Background technique [0002] The skin is the largest organ in the human body. It covers and protects the body and performs many important functions such as perspiration, sensation of heat and cold, and pressure. Skin disease is the most common disease infection in humans of all ages, with a high incidence rate. Diseases of human body functions are often directly manifested on skin tissue, which brings a lot of trouble to patients. However, there are many types of skin diseases, more than 2,000 at present, and many skin diseases are extremely similar and difficult to distinguish, which brings great difficulties to disease diagnosis and easily leads to misdiagnosis. As a non-invasive diagnostic technique, dermoscopy can be used to quickly check suspicio...

AI Technical Summary

Problems solved by technology

On the one hand, the actual clinically collected images contain a lot of noise information such as hair, blood vessels, and black frames; The huge interference makes the problem of skin disease lesion segmentation a practical and challenging problem

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