Workflow for automatic renal perfusion quantification using ASL-MRI and machine learning.

Journal: Magnetic resonance in medicine
PMID:

Abstract

PURPOSE: Clinical applicability of renal arterial spin labeling (ASL) MRI is hampered because of time consuming and observer dependent post-processing, including manual segmentation of the cortex to obtain cortical renal blood flow (RBF). Machine learning has proven its value in medical image segmentation, including the kidneys. This study presents a fully automatic workflow for renal cortex perfusion quantification by including machine learning-based segmentation.

Authors

  • Isabell K Bones
    Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Clemens Bos
    Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Chrit Moonen
    Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Jeroen Hendrikse
    Department of Radiology, UMC Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands.
  • Marijn van Stralen
    Centre for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands.