Continuous Local Histogram Descriptor For Diagnosis of Bronchiolitis Obliterans

Saipullah, Khairul Muzzammil (2011) Continuous Local Histogram Descriptor For Diagnosis of Bronchiolitis Obliterans. In: IEEE Hybrid Intelligence System 2011 (HIS2011), 5-8 December 2011, Ayer keroh, Melaka.

Preview

PDF Continuous_Local_Histogram_Descriptor_For_Diagnosis_of_Bronchiolitis_Obliterans.pdf - Published Version Download (568kB)

Abstract

Texture feature is an important feature analysis method in computer-aided diagnosis systems for disease diagnosis. However, texture feature itself could not provide an overall description of the diseases. In this paper, we propose Continuous Local Feature (CLH) to diagnose the Bronchiolitis Obliterans (BO) lung diseases in the chest computer tomography images. CLH is based on the continuous combination of histograms of local texture feature, local shape feature, and the brightness feature. Because CLH extracts more information, it has high discriminating power and is able to classify between the BO lung disease and normal lung region effectively. The experimental results in classifying between BO and normal lung region show that CLH achieves 98.15% of average sensitivity whereas Local Binary Patterns and Gray Level Run Length Matrix achieve 73% and 75.8% of average sensitivities, respectively. In the receiver operating curve analysis, CLH archives 0.9 of area under curve (AUC) whereas LBP and GLRLM achieve 0.78 and 0.86 of AUCs.

Item Type:	Conference or Workshop Item (Paper)
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Divisions:	Faculty of Electronics and Computer Engineering > Department of Computer Engineering
Depositing User:	Engr. Khairul Muzzammil Saipullah
Date Deposited:	11 Jul 2012 00:04
Last Modified:	28 May 2015 02:39
URI:	http://eprints.utem.edu.my/id/eprint/4098
Statistic Details:	View Download Statistic

Actions (login required)

View Item