Quantitative Analysis of Pulmonary Emphysema using Isotropic Gaussian Markov Random Fields

Chathurika Dharmagunawardhana, Sasan Mahmoodi, Michael Bennett, Mahesan Niranjan

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 achieved.

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Paper Citation


in Harvard Style

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 - Volume 3: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-009-3, pages 44-53. DOI: 10.5220/0004728900440053


in Bibtex Style

@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 - Volume 3: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={44-53},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004728900440053},
isbn={978-989-758-009-3},
}


in EndNote Style

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