Please use this identifier to cite or link to this item: https://idr.l1.nitk.ac.in/jspui/handle/123456789/11366
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dc.contributor.authorSimu, S.-
dc.contributor.authorLal, S.-
dc.contributor.authorNagarsekar, P.-
dc.contributor.authorNaik, A.-
dc.date.accessioned2020-03-31T08:31:13Z-
dc.date.available2020-03-31T08:31:13Z-
dc.date.issued2017-
dc.identifier.citationBiocybernetics and Biomedical Engineering, 2017, Vol.37, 4, pp.718-732en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/11366-
dc.description.abstractBone age is a reliable measure of person's growth and maturation of skeleton. The difference between chronological age and bone age indicates presence of endocrinological problems. The automated bone age assessment system (ABAA) based on Tanner and Whitehouse method (TW3) requires monitoring the growth of radius, ulna and short bones (phalanges) of left hand. In this paper, a detailed analysis of two bones in the bone age assessment system namely, radius and ulna is presented. We propose an automatic extraction method for the region of interest (ROI) of radius and ulna bones from a left hand radiograph (RUROI). We also propose an improved edge-based segmentation technique for those bones. Quantitative and qualitative results of the proposed segmentation technique are evaluated and compared with other state-of-the-art segmentation techniques. Medical experts have also validated the qualitative results of proposed segmentation technique. Experimental results reveal that these proposed techniques provide better segmentation accuracy as compared to the other state-of-the-art segmentation techniques. 2017 Nalecz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciencesen_US
dc.titleFully automatic ROI extraction and edge-based segmentation of radius and ulna bones from hand radiographsen_US
dc.typeArticleen_US
Appears in Collections:1. Journal Articles

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