Automated Segmentation of Substantia Nigra and Red Nucleus in Quantitative Susceptibility Mapping Images

Abstract

Substantia nigra (SN) and red nucleus (RN) located in midbrain are integral in the study of brain disease such as Parkinson's disease (PD). The automatic segmentation of SN and RN in high-resolution quantitative susceptibility mapping (QSM) images can aid in PD characterization and progression. However, only a few methods have been proposed to segment them, owing to the recent development of high quality imaging. Therefore, we describe a novel method for the segmentation of SN and RN in QSM images using contrast enhancement, level set method, wavelet transform and watershed transform. The segmentation performance is evaluated in 20 subjects containing both healthy and PD patients. The results of the proposed segmentation method were closer to the manual segmentation performed by the radiologist than the popular level set methods. The Dice coefficient of the left SN and right SN were 0.77 ± 0.09 and 0.78 ± 0.07 respectively while the Dice for the left RN and right RN were 0.80 ± 0.08 and 0.77 ± 0.08 respectively.