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Authors: Chathurika Dharmagunawardhana 1 ; Sasan Mahmoodi 1 ; Michael Bennett 2 and Mahesan Niranjan 1

Affiliations: 1 University of Southampton, United Kingdom ; 2 University Hospital Southampton NHS Foundation Trust, United Kingdom

Keyword(s): Emphysema, Spatially Varying Parameters, Gaussian Markov Random Fields, Tissue Classification.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Color and Texture Analyses ; Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Image and Video Analysis ; Medical Image Applications

Abstract: A novel texture feature based on isotropic Gaussian Markov random fields is proposed for diagnosis and quantification of emphysema and its subtypes. Spatially varying parameters of isotropic Gaussian Markov random fields are estimated and their local distributions constructed using normalized histograms are used as effective texture features. These features integrate the essence of both statistical and structural properties of the texture. Isotropic Gaussian Markov Random Field parameter estimation is computationally efficient than the methods using other MRF models and is suitable for classification of emphysema and its subtypes. Results show that the novel texture features can perform well in discriminating different lung tissues, giving comparative results with the current state of the art texture based emphysema quantification. Furthermore supervised lung parenchyma tissue segmentation is carried out and the effective pathology extents and successful tissue quantification are ach ieved. (More)

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Paper citation in several formats:
Dharmagunawardhana, C.; Mahmoodi, S.; Bennett, M. and Niranjan, M. (2014). Quantitative Analysis of Pulmonary Emphysema using Isotropic Gaussian Markov Random Fields. In Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 3: VISAPP; ISBN 978-989-758-009-3; ISSN 2184-4321, SciTePress, pages 44-53. DOI: 10.5220/0004728900440053

@conference{visapp14,
author={Chathurika Dharmagunawardhana. and Sasan Mahmoodi. and Michael Bennett. and Mahesan Niranjan.},
title={Quantitative Analysis of Pulmonary Emphysema using Isotropic Gaussian Markov Random Fields},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 3: VISAPP},
year={2014},
pages={44-53},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004728900440053},
isbn={978-989-758-009-3},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 3: VISAPP
TI - Quantitative Analysis of Pulmonary Emphysema using Isotropic Gaussian Markov Random Fields
SN - 978-989-758-009-3
IS - 2184-4321
AU - Dharmagunawardhana, C.
AU - Mahmoodi, S.
AU - Bennett, M.
AU - Niranjan, M.
PY - 2014
SP - 44
EP - 53
DO - 10.5220/0004728900440053
PB - SciTePress

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