Abstract
Medical doctors use various types of technologies to analysis patient different organ like, Magnetic Resonance Imaging, Computed Tomography (CT) scans, X-ray, Endoscopy and others to capture images from the patient body during examination time. Among those imaging technologies, Endoscopy is the most popular imaging technology which is used by most doctors to examine the human digestive system. During the examination time, more than 57,000 images can be generated and the doctor examines the images frame by frame to detect mucosal abnormalities. In fact, this is a tedious and time taking task even for an experienced gastrologist doctor. In this survey paper, different existing abnormal image detection techniques are studied in detail. Recently, detecting different types of diseases from the Capsule Endoscopy and conventional Endoscopy has been an active research area in medical domain. Most of the research has been done aiming to develop self acting algorithms to detect the disease showing by using color, texture analyses, and other techniques. This paper more focuses on abnormality detection techniques.
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Abiko, A.T., Vala, B., Patel, S. (2019). Detecting Mucosal Abnormalities from Wireless Capsule Endoscopy Images. In: Hemanth, J., Fernando, X., Lafata, P., Baig, Z. (eds) International Conference on Intelligent Data Communication Technologies and Internet of Things (ICICI) 2018. ICICI 2018. Lecture Notes on Data Engineering and Communications Technologies, vol 26. Springer, Cham. https://doi.org/10.1007/978-3-030-03146-6_99
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