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Capsule endoscopy (CE) is a preferred diagnostic method for analyzing small bowel diseases. However, capsule endoscopes capturea sparse number of images because of their mechanical limitations. Post-procedural management using computational methodscan enhance image quality. Additional information, including depth, can be obtained by using recently developed computer visiontechniques. It is possible to measure the size of lesions and track the trajectory of capsule endoscopes using the computer visiontechnology, without requiring additional equipment. Moreover, the computational analysis of CE images can help detect lesions moreaccurately within a shorter time. Newly introduced deep leaning-based methods have shown more remarkable results over traditionalcomputerized approaches. A large-scale standard dataset should be prepared to develop an optimal algorithms for improving thediagnostic yield of CE. The close collaboration between information technology and medical professionals is needed.
