Predicting Generalization of AI Colonoscopy Models to Unseen Data

no code implementations • 14 Mar 2024 • Joel Shor, Carson McNeil, Yotam Intrator, Joseph R Ledsam, Hiro-o Yamano, Daisuke Tsurumaru, Hiroki Kayama, Atsushi Hamabe, Koji Ando, Mitsuhiko Ota, Haruei Ogino, Hiroshi Nakase, Kaho Kobayashi, Masaaki Miyo, Eiji Oki, Ichiro Takemasa, Ehud Rivlin, Roman Goldenberg

We test MSN's ability to be trained on data only from Israel and detect unseen techniques, narrow-band imaging (NBI) and chromendoscoy (CE), on colonoscopes from Japan (354 videos, 128 hours).

The unreasonable effectiveness of AI CADe polyp detectors to generalize to new countries

no code implementations • 11 Dec 2023 • Joel Shor, Hiro-o Yamano, Daisuke Tsurumaru, Yotami Intrator, Hiroki Kayama, Joe Ledsam, Atsushi Hamabe, Koji Ando, Mitsuhiko Ota, Haruei Ogino, Hiroshi Nakase, Kaho Kobayashi, Eiji Oki, Roman Goldenberg, Ehud Rivlin, Ichiro Takemasa

$\textbf{Conclusion}$: Differences that prevent CADe detectors from performing well in non-medical settings do not degrade the performance of our AI CADe polyp detector when applied to data from a new country.

Feature-based model selection for object detection from point cloud data

no code implementations • 26 Sep 2022 • Kairi Tokuda, Ryoichi Shinkuma, Takehiro Sato, Eiji Oki

In smart monitoring, object detection from point cloud data acquired by 3D image sensors is implemented for detecting moving objects such as vehicles and pedestrians to ensure safety on the road.

Model Selection Object +2