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Automatic Characterization of the Physiological Condition of the Carotid Artery in 2D Ultrasound Image Sequences Using Spatiotemporal and Spatiospectral 2D Maps.
School of Technology and Health (STH), Royal Institute of Technology (KTH), Alfred Nobels Alle 10, SE-141 52 Huddinge, Sweden.
Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
2014 (Engelska)Ingår i: International Journal of Biomedical Imaging, ISSN 1687-4188, E-ISSN 1687-4196, Vol. 2014, artikel-id 876267Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

A novel method for characterizing and visualizing the progression of waves along the walls of the carotid artery is presented. The new approach is noninvasive and able to simultaneously capture the spatial and the temporal propagation of wavy patterns along the walls of the carotid artery in a completely automated manner. Spatiotemporal and spatiospectral 2D maps describing these patterns (in both the spatial and the frequency domains, resp.) were generated and analyzed by visual inspection as well as automatic feature extraction and classification. Three categories of cases were considered: pathological elderly, healthy elderly, and healthy young cases. Automatic differentiation, between cases of these three categories, was achieved with a sensitivity of 97.1% and a specificity of 74.5%. Two features were proposed and computed to measure the homogeneity of the spatiospectral 2D map which presents the spectral characteristics of the carotid artery wall's wavy motion pattern which are related to the physical, mechanical (e.g., elasticity), and physiological properties and conditions along the artery. These results are promising and confirm the potential of the proposed method in providing useful information which can help in revealing the physiological condition of the cardiovascular system.

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2014. Vol. 2014, artikel-id 876267
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Medicinsk bildbehandling
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URN: urn:nbn:se:uu:diva-336680DOI: 10.1155/2014/876267PubMedID: 24971088OAI: oai:DiVA.org:uu-336680DiVA, id: diva2:1166721
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Correction in: International Journal of Biomedical Imaging, Volume 2017 (2017), Article ID 4237858. https://doi.org/10.1155/2017/4237858

Tillgänglig från: 2017-12-15 Skapad: 2017-12-15 Senast uppdaterad: 2017-12-15Bibliografiskt granskad

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