Automated Detection of Crohn's Disease Intestinal Strictures on Capsule Endoscopy Images Using Deep Neural Networks.

Eyal KlangAna GrinmanShelly SofferReuma Margalit YehudaOranit BarzilayMichal Marianne AmitaiEli KonenShomron Ben-HorinRami EliakimYiftach BarashUri Kopylov

Published in: Journal of Crohn's & colitis (2021)

Deep neural networks are highly accurate in the detection of strictures on CE images in Crohn's disease. The network can accurately separate strictures from ulcers across the severity range. The current accuracy for the detection of ulcers and strictures by deep neural networks may allow for automated detection and grading of Crohn's disease-related findings on CE.

Keyphrases

neural network
deep learning
loop mediated isothermal amplification
label free
real time pcr
machine learning
optical coherence tomography
high resolution
single cell
small bowel
energy transfer