Semi-automated application for kidney motion correction and filtration analysis in MR renography

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Publication Type pre-print
School or College <blank>
Department <blank>
Creator Gerig, Guido
Other Author Rousset, Florian; Vachet, Clement; Conlin, Christopher; Heilbrun, Marta; Zhang, Jeff L.; Lee, Vivian S.
Title Semi-automated application for kidney motion correction and filtration analysis in MR renography
Date 2014-01-01
Description Altered renal function commonly affects patients with cirrhosis, a consequence of chronic liver disease. From lowdose contrast material-enhanced magnetic resonance (MR) renography, we can estimate the Glomerular Filtration Rate (GFR), an important parameter to assess renal function. Two-dimensional MR images are acquired every 2 seconds for approximately 5 minutes during free breathing, which results in a dynamic series of 140 images representing kidney filtration over time. This specific acquisition presents dynamic contrast changes but is also challenged by organ motion due to breathing. Rather than use conventional image registration techniques, we opted for an alternative method based on object detection. We developed a novel analysis framework available under a stand-alone toolkit to efficiently register dynamic kidney series, manually select regions of interest, visualize the concentration curves for these ROIs, and fit them into a model to obtain GFR values. This open-source cross-platform application is written in C++, using the Insight Segmentation and Registration Toolkit (ITK) library, and QT4 as a graphical user interface.
Type Text
Publisher International Society for Magnetic Resonance in Medicine
First Page 4091
Language eng
Bibliographic Citation Rousset, F., Vachet, C., Conlin, C., Heilbrun, M., Zhang, J. L., Lee, V. S., & Gerig, G. (2014). Semi-automated application for kidney motion correction and filtration analysis in MR renography. Proceeding of the 2014 Joint Annual Meeting ISMRM-ESMRMB, 4091.
Rights Management (c)International Society for Magnetic Resonance in Medicine
Format Medium application/pdf
Format Extent 120,343 bytes
Identifier uspace,18965
ARK ark:/87278/s6n61whb
Setname ir_uspace
Date Created 2014-11-06
Date Modified 2021-05-06
ID 712714
Reference URL https://collections.lib.utah.edu/ark:/87278/s6n61whb
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