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Wireless capsule endoscopy is a non-invasive, wireless imaging tool that has developed rapidly over the last several years. One of the main limiting factors using this technology is that it produces a huge number of images, whose analysis, to be done by a doctor, is an extremely time-consuming process. In this research area, the management of this problem has been addressed with the development of Computer-aided Diagnosis systems thanks to which the automatic inspection and analysis of images acquired by the capsule has clearly improved. Recently, a big advance in classification of endoscopic images is achieved with the emergence of deep learning methods. The proposed expert system employs three pre-trained deep convolutional neural networks for feature extraction. In order to construct efficient feature sets, the features from VGG19, InceptionV3 and ResNet50 models are then selected and fused …
Publication date: 
1 Mar 2021
Biblio References: 
Volume: 88 Pages: 101852
Computerized Medical Imaging and Graphics