Abstract #1232
Improvement of Thigh Muscle MRI Image Processing Efficiency using a Batch-Scripted N4ITK Intensity Normalization Algorithm Implemented in 3D Slicer
Prashant Bansal 1 , David Bennett 1 , Xiaodong Tao 1 , and Sally Warner 1
1
Medical Imaging, PAREXEL Informatics,
Billerica, MA, United States
When applied to images with signal inhomogeneity, the
N4ITK algorithm can correct images by use of a
calculated bias field. Herein, we demonstrate that use
of a batch-scripted N4ITK algorithm implemented in
3DSlicer freeware leads to a significantly more
efficient workflow for thigh muscle MR image processing.
Customized automation and N4ITK batch processing through
3DSlicer is possible for efficient image inhomogeneity
correction in large data sets common to clinical
multi-site imaging trials. In addition, the N4ITK
intensity inhomogeneity correction step results in
quicker turnaround and efficient implementation of the
automated and semi-automated segmentation tools
resulting in reliable & faster segmentation in thigh
muscle MRI data sets.
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