Automatic segmentation of the rima glottidis in 4D laryngeal CT scans in Parkinson's disease

Parkinson's disease (PD) is a progressive, incurable neuro-degenerative disease. Symptoms appear when approximately 70% of mid-brain dopaminergic neurons have died. Temporal analysis of the calculated area of the rima glottidis may give an indication of vocal impairment. In this paper, we present an automatic segmentation algorithm to segment the rima glottidis from 4D CT images using texture features and support vector machines (SVM). Automatic two dimensional region growing is then applied as a post processing step to segment the area accurately. The proposed segmentation algorithm resulted in accurate segmentation and we demonstrate a high correlation between the manually segmented area and automatic segmentation.