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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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