Country | : |
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Department | : | Singapore Management University |
Project Title | : | Finding small-bowel lesions: Challenges in endoscopy-image-based learning systems |
Researcher | : | LEE, Youngki , KO, JeongGil , BALAN, Rajesh Krishna , HUYNH, Loc Nguyen , AHN, Jungmo |
Keyword | : | Medical Sciences , Software Engineering |
Publisher | : | Institutional Knowledge at Singapore Management University |
Year End | : | 2018 |
Identifier | : | https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=5056&context=sis_research , https://ink.library.smu.edu.sg/sis_research/4053 |
Source | : | Research Collection School Of Information Systems |
Abstract / Description | : |
Capsule endoscopy identifies damaged areas in a patient's small intestine but often outputs poor-quality images or misses lesions, leading to either misdiagnosis or repetition of the lengthy procedure. The authors propose applying deep-learning models to automatically process the captured images and identify lesions in real time, enabling the capsule to take additional images of a specific location, adjust its focus level, or improve image quality. The authors also describe the technical challenges in realizing a viable automated capsule-endoscopy system. |