NDLI: Automatic detection of tree-in-bud patterns for computer assisted diagnosis of respiratory tract infections

Content Provider	IEEE Xplore Digital Library
Author	Bagci, U. Jianhua Yao Caban, J. Palmore, T.N. Suffredini, A.F. Mollura, D.J.
Copyright Year	2011
Description	Author affiliation: National Library of Medicine (Caban, J.) \|\| Laboratory of Clinical Infectious Diseases (Palmore, T.N.) \|\| Critical Care Medicine Department, of National Institutes of Health (NIH), Bethesda, USA (Suffredini, A.F.) \|\| Department of Radiology and Imaging Sciences (Jianhua Yao) \|\| Center for Infectious Diseases Imaging (Bagci, U.; Mollura, D.J.)
Abstract	Abnormal nodular branching opacities at the lung periphery in Chest Computed Tomography (CT) are termed by radiology literature as tree-in-bud (TIB) opacities. These subtle opacity differences represent pulmonary disease in the small airways such as infectious or inflammatory bronchiolitis. Precisely quantifying the detection and measurement of TIB abnormality using computer assisted detection (CAD) would assist clinical and research investigation of this pathology commonly seen in pulmonary infections. This paper presents a novel method for automatically detecting TIB patterns based on fast localization of candidates using local scale information of the images. The proposed method combines shape index, local gradient statistics, and steerable wavelet features to automatically identify TIB patterns. Experimental results using 39 viral bronchiolitis human para-influenza (HPIV) CTs and 21 normal lung CTs achieved an overall accuracy of 89.95%.
Starting Page	5096
Ending Page	5099
File Size	802668
Page Count	4
File Format	PDF
ISBN	9781424441211
ISSN	1557170X
e-ISBN	9781457715891
e-ISBN	9781424441228
DOI	10.1109/IEMBS.2011.6091262
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-08-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Feature extraction Shape Silicon Lungs Design automation Diseases Computed tomography
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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