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Volume & Issue no: Volume 3, Issue 12, December 2014

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Title:
Texture-Based Identification and Characterization of Pneumonia Patterns in Lung
Author Name:
Mr. Anup R. Aswar, Ms. Kunda P. Nagarikar, and Prof. Pragati D. Pawar
Abstract:
ABSTRACT Identification and characterization of diffuse parenchyma lung disease (DPLD) patterns is very difficult so an automated scheme for volumetric quantification of interstitial pneumonia (IP) patterns, a subset of DPLD, is presented, utilizing a multi detector CT (MDCT) dataset. Firstly, lung-field segmentation is achieved by 3-D automated gray-level Thresholding combined with an edge-highlighting wavelet pre- processing step, followed by a texture-based border refinement step. The vessel tree volume is identified and removed from lung field, resulting in lung parenchyma (LP) volume. Identification and characterization of IP patterns is formulated as a three-class pattern classification of LP into normal, ground glass, and reticular patterns, by means of k-nearest neighbour voxel classification, exploiting 3-D co-occurrence features. Performance of the proposed scheme in identifying and characterizing ground glass and reticular patterns was evaluated by means of volume overlap.
Cite this article:
Mr. Anup R. Aswar, Ms. Kunda P. Nagarikar, and Prof. Pragati D. Pawar , " Texture-Based Identification and Characterization of Pneumonia Patterns in Lung" , International Journal of Application or Innovation in Engineering & Management (IJAIEM) , Volume 3, Issue 12, December 2014 , pp. 284-290 , ISSN 2319 - 4847.
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