EndoUDA: a modality independent segmentation approach for endoscopy imaging
Gastrointestinal (GI) cancer precursors require frequent monitoring for risk stratification of patients. Automated segmentation methods can help to assess risk areas more accurately, and assist in therapeutic procedures or even removal. In clinical practice, addition to the conventional white-light...
Main Authors: | Celik, N, Ali, S, Gupta, S, Braden, B, Rittscher, J |
---|---|
Format: | Conference item |
Language: | English |
Published: |
Springer Nature
2021
|
Similar Items
-
Uda & Dara /
by: Aisya Sofea, author 278181
Published: (2011) -
EndoConf: real-time video consultation during endoscopy; telemedicine in endoscopy at its best
by: Ulrik Deding, et al.
Published: (2021-11-01) -
A deep learning framework for quality assessment and restoration in video endoscopy
by: Ali, S, et al.
Published: (2020) -
Additive angular margin for few shot learning to classify clinical endoscopy images
by: Ali, S, et al.
Published: (2020) -
Indian Association of Gastrointestinal Endo Surgeons COVID-19 endoscopy recommendations
by: Easwaramoorthy Sundaram, et al.
Published: (2020-01-01)