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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Bibliographic Details
Published in:	Medical physics (Lancaster) Vol. 46; no. 10; pp. 4417 - 4430
Main Authors:	Huang, Wenjian, Li, Hao, Wang, Rui, Zhang, Xiaodong, Wang, Xiaoying, Zhang, Jue
Format:	Journal Article
Language:	English
Published:	United States 01.10.2019
Subjects:	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
Online Access:	Get full text
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