Multi-Scale Supervised 3D U-Net for Kidneys and Kidney Tumor Segmentation

Accurate segmentation of kidneys and kidney tumors is an essential step for radiomic analysis as well as developing advanced surgical planning techniques. In clinical analysis, the segmentation is currently performed by clinicians from the visual inspection images gathered through a computed tomogra...

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Veröffentlicht in:	arXiv.org 2020-04
Hauptverfasser:	Zhao, Wenshuai, Jiang, Dihong, Jorge Peña Queralta, Westerlund, Tomi
Format:	Artikel
Sprache:	eng
Schlagworte:	Architecture Computed tomography Computer Science - Learning Datasets Heterogeneity Image segmentation Inspection Kidneys Machine learning Medical imaging Multiscale analysis Statistics - Machine Learning Tumors
Online-Zugang:	Volltext
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