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Quantitative analysis of pulmonary emphysema using isotropic Gaussian Markov random fields

Quantitative analysis of pulmonary emphysema using isotropic Gaussian Markov random fields
Quantitative analysis of pulmonary emphysema using isotropic Gaussian Markov random fields
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.
44-53
Dharmagunawardhana, Chathurika
68c6fe3a-ccce-4580-91ee-ec73fc2f9d07
Mahmoodi, Sasan
91ca8da4-95dc-4c1e-ac0e-f2c08d6ac7cf
Bennett, Michael
6df5585a-3d93-4870-8797-389759fc82c7
Niranjan, Mahesan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f
Dharmagunawardhana, Chathurika
68c6fe3a-ccce-4580-91ee-ec73fc2f9d07
Mahmoodi, Sasan
91ca8da4-95dc-4c1e-ac0e-f2c08d6ac7cf
Bennett, Michael
6df5585a-3d93-4870-8797-389759fc82c7
Niranjan, Mahesan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f

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

Record type: Conference or Workshop Item (Paper)

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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Published date: January 2014
Venue - Dates: 9th International Conference on Computer Vision Theory and Applications, Lisbon, Portugal, 2014-01-05 - 2014-01-08
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 360198
URI: http://eprints.soton.ac.uk/id/eprint/360198
PURE UUID: 4f7ddf73-a5d8-43d3-b6b8-c7ddaa864ccd
ORCID for Mahesan Niranjan: ORCID iD orcid.org/0000-0001-7021-140X

Catalogue record

Date deposited: 28 Nov 2013 14:23
Last modified: 15 Mar 2024 03:29

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Contributors

Author: Chathurika Dharmagunawardhana
Author: Sasan Mahmoodi
Author: Michael Bennett
Author: Mahesan Niranjan ORCID iD

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