Medical Faculty Mannheim, Mannheim Institute for Intelligent Systems in Medicine, Computer Assisted Clinical Medicine, Heidleberg University, Mannheim, Germany
Department of Biomedicine, Mohn Medical Imaging and Visualization Centre, University of Bergen, Bergen, Norway
Laura Hansen
Medical Faculty Mannheim, Mannheim Institute for Intelligent Systems in Medicine, Computer Assisted Clinical Medicine, Heidleberg University, Mannheim, Germany
Medical Faculty Mannheim, Mannheim Institute for Intelligent Systems in Medicine, Computer Assisted Clinical Medicine, Heidleberg University, Mannheim, Germany
Magnetic resonance imaging has achieved an increasingly important role in the clinical work-up of renal diseases such chronic kidney disease (CKD). A large panel of parameters have been proposed to diagnose CKD among them total kidney volume (TKV) which recently qualified as biomarker. Volume estimation in renal MRI is based on image segmentation of the kidney and/or its compartments. Beyond volume estimation renal segmentation supports also the quantification of other MR based parameters such as perfusion or filtration. The aim of the present article is to discuss the recent existing literature on renal image segmentation techniques and show today’s limitations of the proposed techniques that might hinder clinical translation. We also provide pointers to open source software related to renal image segmentation.
