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Weakly supervised segmentation of tumor lesions in PET-CT hybrid imaging

Purpose: We introduce and evaluate deep learning methods for weakly supervised segmentation of tumor lesions in whole-body fluorodeoxyglucose-positron emission tomography (FDG-PET) based solely on binary global labels (“tumor” versus “no tumor”). Approach: We propose a three-step approach based on (...

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Detalles Bibliográficos
Autores principales:	Früh, Marcel, Fischer, Marc, Schilling, Andreas, Gatidis, Sergios, Hepp, Tobias
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Society of Photo-Optical Instrumentation Engineers 2021
Materias:	Image Processing
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8510879/ https://www.ncbi.nlm.nih.gov/pubmed/34660843 http://dx.doi.org/10.1117/1.JMI.8.5.054003

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