A self‐supervised strategy for fully automatic segmentation of renal dynamic contrast‐enhanced magnetic resonance images

Purpose An automated accurate segmentation for dynamic contrast‐enhanced magnetic resonance (DCE‐MR) image sequences is essential for quantification of renal function. A self‐supervised strategy is proposed for fully automatic segmentation of the renal DCE‐MR images without using manually labeled da...

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Vydané v:	Medical physics (Lancaster) Ročník 46; číslo 10; s. 4417 - 4430
Hlavní autori:	Huang, Wenjian, Li, Hao, Wang, Rui, Zhang, Xiaodong, Wang, Xiaoying, Zhang, Jue
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States 01.10.2019
Predmet:	automatic kidney segmentation Automation Contrast Media DCE‐MRI Female Humans Image Processing, Computer-Assisted - methods Kidney - diagnostic imaging Magnetic Resonance Imaging Male Middle Aged random walker self‐supervised algorithm Supervised Machine Learning unsupervised algorithm random walker DCE-MRI self-supervised algorithm unsupervised algorithm automatic kidney segmentation
ISSN:	0094-2405, 2473-4209, 2473-4209
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