Abstract #1465

Automatic spinal cord segmentation in pediatric MR images

Colline Blanc^1,2, Shiva Shahrampour³, Feroze Mohamed³, and Benjamin De Leener^1,2,4

¹NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montreal, QC, Canada, Montreal, QC, Canada, ²Research Center, Ste-Justine Hospital University Centre, Montreal, QC, Canada, Montreal, QC, Canada, ³Thomas Jefferson University, Philadelphia, PA, United States, Philadelphia, PA, United States, ⁴Department of Computer and Software Engineering, Polytechnique Montréal, Montréal, QC, Canada, Montreal, QC, Canada

Synopsis

Segmentation of the spinal cord is an essential process for the accurate delineation of spinal cord structures. However, it is a long process and automatic segmentation tools are not adapted to segment the pediatric spinal cord. We therefore developed a tool mixing a neural network and a deterministic method to overcome the limitations. We succeeded in obtaining a segmentation with a dice coefficient of 0.86 on a patient with a spinal cord injury (SCI).

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