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Fat quantification in MRI-defined lumbar muscles

Antony, Joseph orcid logoORCID: 0000-0001-6493-7829, McGuinness, Kevin orcid logoORCID: 0000-0003-1336-6477, Welch, Neil, Coyle, Joe, Franklyn-Miller, Andrew orcid logoORCID: 0000-0002-7826-2209, O'Connor, Noel E. orcid logoORCID: 0000-0002-4033-9135 and Moran, Kieran orcid logoORCID: 0000-0003-2015-8967 (2014) Fat quantification in MRI-defined lumbar muscles. In: 4th International Conference on Image Processing Theory, Tools and Applications, 14-17 Oct 2014, Paris, France.

Abstract
Some studies suggest fat infiltration in the lumbar muscles (LM) is associated with lower back pain (LBP) in adults. Usually fat in MRI-defined lumbar muscles is qualitatively valuated by visual grading via a 3 point scale, whereas a quantitative continuous (0 - 100%) approach may provide a greater insight. In this paper, we propose a method to precisely quantify the fat content / infiltration in a user-defined region of the lumbar muscles, which may aid better diagnosis. The key steps are segmenting the region of interest (ROI) from the lumbar muscles, identifying the fatty regions in the segmented region based on the selected threshold and softness levels, computing the parameters (such as total and region-wise fat content percentage, total-cross sectional area (TCSA), functional cross- sectional area (FCSA)) and exporting the computations and associated patient information from the MRI, into a atabase. A standalone application using MATLAB R2010a was developed to perform the required computations along with an intuitive GUI.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:Fat infiltration; Lumbar muscles; Region of interest; Region-wise segmentation; Fat percentage; Graphical user interface
Subjects:Medical Sciences > Sports sciences
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Science and Health > School of Health and Human Performance
Research Initiatives and Centres > INSIGHT Centre for Data Analytics
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:19994
Deposited On:16 Oct 2014 13:47 by Joseph Antony . Last Modified 12 Aug 2020 13:22
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