Share Email Print

Proceedings Paper

Multiscale intensity homogeneity transformation method and its application to computer-aided detection of pulmonary embolism in computed tomographic pulmonary angiography (CTPA)
Author(s): Yanhui Guo; Chuan Zhou; Heang-Ping Chan; Jun Wei; Aamer Chughtai; Baskaran Sundaram; Lubomir M. Hadjiiski; Smita Patel; Ella A. Kazerooni
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

A 3D multiscale intensity homogeneity transformation (MIHT) method was developed to reduce false positives (FPs) in our previously developed CAD system for pulmonary embolism (PE) detection. In MIHT, the voxel intensity of a PE candidate region was transformed to an intensity homogeneity value (IHV) with respect to the local median intensity. The IHVs were calculated in multiscales (MIHVs) to measure the intensity homogeneity, taking into account vessels of different sizes and different degrees of occlusion. Seven new features including the entropy, gradient, and moments that characterized the intensity distributions of the candidate regions were derived from the MIHVs and combined with the previously designed features that described the shape and intensity of PE candidates for the training of a linear classifier to reduce the FPs. 59 CTPA PE cases were collected from our patient files (UM set) with IRB approval and 69 cases from the PIOPED II data set with access permission. 595 and 800 PEs were identified as reference standard by experienced thoracic radiologists in the UM and PIOPED set, respectively. FROC analysis was used for performance evaluation. Compared with our previous CAD system, at a test sensitivity of 80%, the new method reduced the FP rate from 18.9 to 14.1/scan for the PIOPED set when the classifier was trained with the UM set and from 22.6 to 16.0/scan vice versa. The improvement was statistically significant (p<0.05) by JAFROC analysis. This study demonstrated that the MIHT method is effective in reducing FPs and improving the performance of the CAD system.

Paper Details

Date Published: 1 April 2013
PDF: 6 pages
Proc. SPIE 8670, Medical Imaging 2013: Computer-Aided Diagnosis, 867036 (1 April 2013); doi: 10.1117/12.2008053
Show Author Affiliations
Yanhui Guo, Univ. of Michigan Health System (United States)
Chuan Zhou, Univ. of Michigan Health System (United States)
Heang-Ping Chan, Univ. of Michigan Health System (United States)
Jun Wei, Univ. of Michigan Health System (United States)
Aamer Chughtai, Univ. of Michigan Health System (United States)
Baskaran Sundaram, Univ. of Michigan Health System (United States)
Lubomir M. Hadjiiski, Univ. of Michigan Health System (United States)
Smita Patel, Univ. of Michigan Health System (United States)
Ella A. Kazerooni, Univ. of Michigan Health System (United States)

Published in SPIE Proceedings Vol. 8670:
Medical Imaging 2013: Computer-Aided Diagnosis
Carol L. Novak; Stephen Aylward, Editor(s)

© SPIE. Terms of Use
Back to Top