Refining weak supervision for robust lung cavity segmentation: A graph-affinity method with boundary constraints.

Pixel-level annotation of lung cavities (LCs) in computed tomography (CT) images is challenging due to their morphological diversity and complexity. Weakly supervised semantic segmentation (WSSS) methods, which utilize sparse annotations (e.g., image-level labels), offer a promising solution. Howeve...

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Bibliografische Detailangaben

Hauptverfasser:	Zeyu Ding, Zhuoyi Tan, Hizmawati Madzin, Zhengdong Li, Juntao Liu
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	Public Library of Science (PLoS) 2026-01-01
Schriftenreihe:	PLoS ONE
Online-Zugang:	https://doi.org/10.1371/journal.pone.0341717
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