@article{Mendez_El-Zehiry_Zapirain_Elmaghraby_2024, title={Pathological Vocal Folds Features extraction using a modified Active Contour Segmentation}, volume={4}, url={https://oiccpress.com/Majlesi-Journal-of-Electrical-Engineering/article/pathological-vocal-folds-features-extraction-using-a-modified-active-contour-segmentation/}, DOI={10.1234/mjee.v4i4.387}, abstractNote={This paper presents the study of vocal videostroboscopic videos to detect morphological pathologies using an active contour segmentation and objective measurements. The ad-hoc designed active contour algorithm permits to obtain a robust and fast segmentation using vocal folds images in RGB format. In this work, we have employed connected component analysis as a post-processing tool. After the segmentation process the image is analyzed and the pathology can be localized automatically and we can extract some features of each fold (such as the size of the polyp or cyst, the glottal space, the position…). Experimental results demonstrate that the proposed method is effective. Our proposal segments correctly the 95% of database test videos and it shows a great advance in design. The objective measurements complete a new method to diagnose vocal folds pathologies.}, number={4}, journal={Majlesi Journal of Electrical Engineering}, publisher={OICC Press}, author={Mendez, Amaia and El-Zehiry, Noha and Zapirain, Begoña García and Elmaghraby, Adel}, year={2024}, month={Feb.}, keywords={Active Contour Model, Objective Measurements. Videoendoscopy, Benign Pathologies, Segmentation, Technology} }