Predicting semantic segmentation quality in laryngeal endoscopy images

Endoscopy is a major tool for assessing the physiology of inner organs. Contemporary artificial intelligence methods are used to fully automatically label medical important classes on a pixel-by-pixel level. This so-called semantic segmentation is for example used to detect cancer tissue or to asses...

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Bibliographic Details
Published in:	PloS one Vol. 20; no. 7; p. e0314573
Main Authors:	Kist, Andreas M., Razi, Sina, Groh, René, Gritsch, Florian, Schützenberger, Anne
Format:	Journal Article
Language:	English
Published:	United States Public Library of Science 03.07.2025 Public Library of Science (PLoS)
Subjects:	Algorithms Analysis Artificial Intelligence Biology and Life Sciences Computer and Information Sciences Datasets Deep learning Endoscopy Engineering and Technology Humans Image processing Image Processing, Computer-Assisted - methods Image quality Image segmentation Laryngoscopy Laryngoscopy - methods Larynx - diagnostic imaging Masks Medical imaging Medicine and Health Sciences Methods Neural networks Physiology Pixels Semantic segmentation Semantics Social Sciences Subject specialists Traffic signals Germany
ISSN:	1932-6203, 1932-6203
Online Access:	Get full text
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