Abstract
Background: Challenges in visual identification of laryngeal disorders lead researchers
to investigate new opportunities to help clinical examination. This paper presents an efficient and
simple method which extracts and assesses blood vessels on vocal fold tissue in order to serve
medical diagnosis.
Methods: The proposed vessel segmentation approach has been designed in order to overcome difficulties
raised by design specifications of videolaryngostroboscopy and anatomic structure of vocal
fold vasculature. The limited number of medical studies on vocal fold vasculature point out that
the direction of blood vessels and amount of vasculature are discriminative features for vocal fold
disorders. Therefore, we extracted the features of vessels on the basis of these studies. We represent
vessels as vascular vectors and suggest a vector field based measurement that quantifies the
orientation pattern of blood vessels towards vocal fold pathologies.
Results: In order to demonstrate the relationship between vessel structure and vocal fold disorders,
we performed classification of vocal fold disorders by using only vessel features. A binary tree of
Support Vector Machine (SVM) has been exploited for classification. Average recall of proposed
vessel extraction method was calculated as 0.82 while healthy, sulcus vocalis, laryngitis classification
accuracy of 0.75 was achieved.
Conclusion: Obtained success rates showed the efficiency of vocal fold vessels in serving as an
indicator of laryngeal diseases.
Keywords:
Laryngeal image analysis, vascular vectors, vessel centerline extraction, vocal fold pathologies, histogram of oriented
gradients, matched filter.
Graphical Abstract
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