Please use this identifier to cite or link to this item: https://idr.nitk.ac.in/jspui/handle/123456789/7430
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dc.contributor.authorMadipalli, P.
dc.contributor.authorKotta, S.
dc.contributor.authorDadi, H.
dc.contributor.authorNagaraj, Y.
dc.contributor.authorAsha, C.S.
dc.contributor.authorNarasimhadhan, A.V.
dc.date.accessioned2020-03-30T09:59:05Z-
dc.date.available2020-03-30T09:59:05Z-
dc.date.issued2019
dc.identifier.citation2018 24th National Conference on Communications, NCC 2018, 2019, Vol., , pp.-en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/7430-
dc.description.abstractCardiovascular diseases have been one of the leading causes of death and have been increasing in much of the developing world. Atherosclerosis, the accumulation of plaque on artery walls is the major for cardiovascular diseases. This is diagnosed by measuring the thickness of IMC of common carotid artery (CCA) in ultrasound images. In this paper, we present a completely automatic technique for segmentation of IMC in ultrasound images of CCA. The image is segmented using adaptive wind driven optimization (AWDO) technique. The denoising filter based on Bayesian least square approach and a robust enhancement technique is used in the pre-processing stage. The proposed method is evaluated on 60 ultrasound images and is compared with the state-of-The-Art methods. The experimental results show that the proposed method yields better results as compared to other methods. � 2018 IEEE.en_US
dc.titleAutomatic Segmentation of Intima Media Complex in Common Carotid Artery using Adaptive Wind Driven Optimizationen_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

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