Colposcopic Image Segmentation Based on Feature Refinement and Attention

The current computer-aided diagnosis for cervical cancer screening encounters issues with missing detailed information during colposcopic image segmentation and incomplete edge delineation. To overcome these challenges, this study introduces the RUC-U2Net architecture, which enhances image segmentat...

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Veröffentlicht in:	IEEE access 2024, Vol.12, p.40856-40870
Hauptverfasser:	He, Yuxi, Liu, Liping, Wang, Jinliang, Zhao, Nannan, He, Hangyu
Format:	Artikel
Sprache:	eng
Schlagworte:	Biomedical imaging Cervical cancer colposcopy image Computer architecture Datasets Decoders Feature maps feature refinement Image edge detection Image segmentation lightweight upsampling loss function Medical diagnostic imaging Medical imaging Medical screening Performance measurement Solid modeling
Online-Zugang:	Volltext
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