Bleeding classification of enhanced wireless capsule endoscopy images using deep convolutional neural network

• Main Authors: Rosdiana, Shahril, Saito, Atsushi, Shimizu, Akinobu, Sabariah, Baharun
• 格式: Article
• 语言: English
• 出版: Institute of Information Science 2020
• 主题: QA76 Computer software
• 在线阅读: http://umpir.ump.edu.my/id/eprint/26711/1/Bleeding%20classification%20of%20enhanced%20wireless%20capsule%20endoscopy%20images%20.pdf; http://umpir.ump.edu.my/id/eprint/26711/; http://jise.iis.sinica.edu.tw/JISESearch/pages/View/PaperView.jsf?keyId=172_2294

This paper investigates the performance of a Deep Convolutional Neural Network (DCNN) algorithm to identify bleeding areas of wireless capsule endoscopy (WCE) images without known prior knowledge of bleeding and normal features of the images. In this study, a pre-processing technique has been propos...