Affiliations:
Institute of Computer Science, Romanian Academy Iaşi Branch, Iaşi, Romania
Correspondence:
[*]
Corresponding author. Mihaela Luca. Institute of Computer Science, Romanian Academy Iaşi Branch, 8, Bd. Carol I, Iaşi, Romania. E-mail: [email protected].
Abstract: Video colonoscopy automatic processing is a challenge and further development of computer assisted diagnosis is very helpful in correctness assessment of the exam, in e-learning and training, for statistics on polyps’ malignity or in polyps’ survey. New devices and programming languages are emerging and deep learning begun already to furnish astonishing results, in the quest for high speed and optimal polyp detection software. This paper presents a successful attempt in detecting the intestinal polyps in real time video colonoscopy with deep learning, using Mobile Net.
Keywords: Video colonoscopy, polyp detection, deep learning, real time
