Abstract #4724

Automated Segmentation of Substantia Nigra in Neuromelanin-Sensitive Magnetic Resonance Imaging

Touseef Ahmad Qureshi¹, Cody Lynch¹, Elliot Hogg², Tina Wu³, Michele Tagliati³, Debiao Li¹, and Zhaoyang Fan¹

¹Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States, ²Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, United States, ³Cedars-Sinai Medical Center, Los Angeles, CA, United States

Accurate segmentation of Substantia Nigra (SN) in Neuromelanin-Sensitive MRI (NM-MRI) is a prerequisite for efficient quantification and evaluation of severity of Parkinson disease. We present a fully automated algorithm for localization and segmentation of SN in NM-MRI. The localization algorithm uses a new specialized template matching model consisting of a resizable cardioid plane. The segmentation of SN is performed using freeform active contour segmentation model. The system is tested on 19 NM-MRI scans (10 healthy volunteers and 9 patients with Parkinson disease), acquired using 3T MRI system. The success rate for localization is 98.2%, whilst dice coefficient for segmentation reaches 0.89.

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