Impact of Image Resolution on Deep Learning Performance in Endoscopy Image Classification: An Experimental Study Using a Large Dataset of Endoscopic Images

Recent trials have evaluated the efficacy of deep convolutional neural network (CNN)-based AI systems to improve lesion detection and characterization in endoscopy. Impressive results are achieved, but many medical studies use a very small image resolution to save computing resources at the cost of...

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Veröffentlicht in:	Diagnostics (Basel) Jg. 11; H. 12; S. 2183
Hauptverfasser:	Thambawita, Vajira, Strümke, Inga, Hicks, Steven A., Halvorsen, Pål, Parasa, Sravanthi, Riegler, Michael A.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI AG 24.11.2021 MDPI
Schlagworte:	Automation Classification convolutional neural networks Datasets Deep learning endoscopic images Endoscopy Experiments image resolution Neural networks Performance evaluation endoscopic images image resolution convolutional neural networks
ISSN:	2075-4418, 2075-4418
Online-Zugang:	Volltext
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