Deep Learning for Bleeding Detection in Endoscopic Capsule Images
Publish place: International Congress on Science and Engineering
Publish Year: 1396
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
GERMANCONF01_060
تاریخ نمایه سازی: 26 مرداد 1397
Abstract:
This paper discusses an algorithm for detecting bleeding in images taken from anendoscopic capsule. This algorithm consists of two parts. First, with deep learning,they instruct a deep network to distinguish between blood images and normal images.Then the images in the blood class are transmitted to the second part of the algorithm.In the second part, the images are converted to HSV and by comparing each pixel withthe threshold of blood, the location of the bleeding is marked and indicated by a greenrectangle. Simulation of this algorithm is implemented using the Python language andTensorflow. The results indicate that the deep network has been able to categorizewell between blood images and normal images, and the location of bleeding is alsoprominently indicated.
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Authors
Mohammad Hasan Olyaei Torqabeh
Faculty of Electrical Engineering, Sadjad University of Technology, Mashhad, Iran
Ali Olyaei Torqabeh
Department of Computer Engineering, Faculty of Engineering, Ferdowsi University ofMashhad, Mashhad, Iran