Quantitative analysis of pulmonary emphysema using isotropic Gaussian Markov random fields


Dharmagunawardhana, Chathurika, Mahmoodi, Sasan, Bennett, Michael and Niranjan, Mahesan (2014) Quantitative analysis of pulmonary emphysema using isotropic Gaussian Markov random fields At 9th International Conference on Computer Vision Theory and Applications, Portugal. 05 - 08 Jan 2014. , pp. 44-53.

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Description/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.

Item Type: Conference or Workshop Item (Paper)
Venue - Dates: 9th International Conference on Computer Vision Theory and Applications, Portugal, 2014-01-05 - 2014-01-08
Related URLs:
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Organisations: Southampton Wireless Group
ePrint ID: 360198
Date :
Date Event
January 2014Published
Date Deposited: 28 Nov 2013 14:23
Last Modified: 17 Apr 2017 14:34
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/360198

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