Automated diagnostic System for laryngeal hemiplegia using endoscopic image

Laryngeal hemiplegia is a naturally occurring disease of a horse recognized as a common reason of the poor performance. This syndrome is diagnosed by a human through an endoscopic observation. The asymmetry of arytenoid cartilages is calculated by left to right anglequotients (LRQ). However, human inspection may misdiagnose the disease. Therefore, an automatic diagnostic system is expected to analysis the asymmetric view of laryngeal hemiplegia. In this paper, we have proposed an automatic way to analysis laryngeal hemiplegia by combining image segmentation and parabola fitting algorithms. Our method includes six steps: (1) hierarchicalcontour map is achieved by a state-of-the-art hierarchicalimage segmentation method joining Global Probability of Boundary (gPb), Oriented Watershed Transform (OWT),and Ultrametric Contour Map (UCM); (2) key curves areextracted; (3) boundaries are confirmed by Parabola fittingmethod; (4) dorsal-most point of rima glottidis is selected; (5)proximal-most point is identified and (6) LRQ is calculatedas the final measurement. To evaluate the accuracy of ourproposed method, a dataset of horse larynx endoscopicimages has been built up and tested. Experimental results have shown that the proposed method has good performance.