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

Ulas Baǧci*, Jianhua Yao, Jesus Caban, Tara N. Palmore, Anthony F. Suffredini, Daniel J. Mollura

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

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%.

Original languageEnglish (US)
Title of host publication33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Pages5096-5099
Number of pages4
DOIs
StatePublished - 2011
Externally publishedYes
Event33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 - Boston, MA, United States
Duration: Aug 30 2011Sep 3 2011

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Other

Other33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
CountryUnited States
CityBoston, MA
Period8/30/119/3/11

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Fingerprint Dive into the research topics of 'Automatic detection of tree-in-bud patterns for computer assisted diagnosis of respiratory tract infections'. Together they form a unique fingerprint.

Cite this