Abstract
This paper introduces a fully automated segmentation scheme for carotid artery ultrasound images. The proposed scheme is based on fuzzy c-means clustering. It consists of four major stages. These stages are pre-processing, feature extraction, fuzzy c-means clustering, and finally boundary extraction. Experimental results demonstrated the efficiency of the proposed scheme in segmenting carotid artery ultrasound images.
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Abdel-Dayem, A.R., El-Sakka, M.R. (2007). Fuzzy C-Means Clustering for Segmenting Carotid Artery Ultrasound Images. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2007. Lecture Notes in Computer Science, vol 4633. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74260-9_83
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DOI: https://doi.org/10.1007/978-3-540-74260-9_83
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74258-6
Online ISBN: 978-3-540-74260-9
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