Cargando…
Improving Temporal Stability and Accuracy for Endoscopic Video Tissue Classification Using Recurrent Neural Networks
Early Barrett’s neoplasia are often missed due to subtle visual features and inexperience of the non-expert endoscopist with such lesions. While promising results have been reported on the automated detection of this type of early cancer in still endoscopic images, video-based detection using the te...
Autores principales: | Boers, Tim, van der Putten, Joost, Struyvenberg, Maarten, Fockens, Kiki, Jukema, Jelmer, Schoon, Erik, van der Sommen, Fons, Bergman, Jacques, de With, Peter |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7436238/ https://www.ncbi.nlm.nih.gov/pubmed/32722344 http://dx.doi.org/10.3390/s20154133 |
Ejemplares similares
-
Machine learning in GI endoscopy: practical guidance in how to interpret a novel field
por: van der Sommen, Fons, et al.
Publicado: (2020) -
The Argos project: The development of a computer-aided detection
system to improve detection of Barrett's neoplasia on white light
endoscopy
por: de Groof, Jeroen, et al.
Publicado: (2019) -
Towards a robust and compact deep learning system for primary detection of early Barrett’s neoplasia: Initial image‐based results of training on a multi‐center retrospectively collected data set
por: Fockens, Kiki N., et al.
Publicado: (2023) -
Linked color imaging improves identification of early gastric cancer lesions by expert and non-expert endoscopists
por: Fockens, Kiki, et al.
Publicado: (2022) -
Algorithm combining virtual chromoendoscopy features for colorectal polyp classification
por: Schreuder, Ramon-Michel, et al.
Publicado: (2021)