Medical image recognition based on VGGNet19

Abstract

Gastrointestinal diseases are one of the common clinical diseases, which often require medical imaging for diagnosis and treatment. Recently, the development of deep learning technology has promoted the development of medical image recognition, which provides new ideas and methods for the automatic recognition and analysis of medical images. VGGNet19 is a convolutional neural network model that has attracted much attention because of its simple structure, easy training and better recognition effect. For this reason, this paper proposes an improved VGGNet19 model for medical image recognition of gastrointestinal diseases. Specifically, the project adds an additional fully connected layer and Dropout layer on top of the built VGGNet19 to achieve the recognition of medical images of stomach diseases. Extensive experiments on standard medical stomach images show that the proposed method improves the recognition performance to a certain extent.