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Emphysema Region Pre-Detection Method for Emphysema Disease Diagnosis using Lung CT Images
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논문 기본 정보

Type
Proceeding
Author
Khairul Muzzammil Saipullah (인하대학교) Shao-Hu Peng (인하대학교) Min-Wook Park (인하대학교) Deok-Hwan Kim (인하대학교)
Journal
Korean Institute of Information Scientists and Engineers 한국정보과학회 학술발표논문집 Vol.37 No.1C
Published
2010.6
Pages
447 - 451 (5page)

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Emphysema Region Pre-Detection Method for Emphysema Disease Diagnosis using Lung CT Images
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In this paper, we propose a simple but effective algorithm to increase the speed of Emphysema region classification. Emphysema region classification method based on CT image consumes a lot of time because of the large number of subregions due to the large size of CT image. Some of the sub-regions contain no Emphysema and the classification of these regions is worthless. To speed up the classification process, we create an algorithm to select Emphysema region candidates and only use these candidates in the Emphysema region classification instead of all of the sub-regions. First, the lung region is detected. Then we threshold the lung region and only select the dark pixels because Emphysema only appeared in the dark area of the CT image. Then the thresholded pixels are clustered into a region that called the Emphysema pre-detected region or Emphysema region candidate. This region is then divided into sub-region for the Emphysema region classification. The experimental result shows that Emphysema region classification using predetected Emphysema region decreases the size of lung region which will result in about 84.51% of time reduction in Emphysema region classification.

Contents

Abstract
1. Introduction
2. Related Works
3. Proposed Method
4. Experimental Results
5. Conclusion and Future Works
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UCI(KEPA) : I410-ECN-0101-2010-569-003118962