Automated detection of nodules attached to the pleural and mediastinal surface in low-dose CT scans

Bram van Ginneken; Andre Tan; Keelin Murphy; Bart-Jan de Hoop; Mathias Prokop

doi:10.1117/12.772298

17 March 2008 Automated detection of nodules attached to the pleural and mediastinal surface in low-dose CT scans

Bram van Ginneken, Andre Tan, Keelin Murphy, Bart-Jan de Hoop, Mathias Prokop

Proceedings Volume 6915, Medical Imaging 2008: Computer-Aided Diagnosis; 69150X (2008) https://doi.org/10.1117/12.772298
Event: Medical Imaging, 2008, San Diego, California, United States

Abstract

This paper presents a new computer-aided detection scheme for lung nodules attached to the pleural or mediastinal surface in low dose CT scans. First the lungs are automatically segmented and smoothed. Any connected set of voxels attached to the wall - with each voxel above minus 500 HU and the total object within a specified volume range - was considered a candidate finding. For each candidate, a refined segmentation was computed using morphological operators to remove attached structures. For each candidate, 35 features were defined, based on their position in the lung and relative to other structures, and the shape and density within and around each candidate. In a training procedure an optimal set of 15 features was determined with a k-nearest-neighbor classifier and sequential floating forward feature selection. The algorithm was trained with a data set of 708 scans from a lung cancer screening study containing 224 pleural nodules and tested on an independent test set of 226 scans from the same program with 58 pleural nodules. The algorithm achieved a sensitivity of 52% with an average of 0.76 false positives per scan. At 2.5 false positive marks per scan, the sensitivity increased to 80%.

Citation Download Citation

Bram van Ginneken, Andre Tan, Keelin Murphy, Bart-Jan de Hoop, and Mathias Prokop "Automated detection of nodules attached to the pleural and mediastinal surface in low-dose CT scans", Proc. SPIE 6915, Medical Imaging 2008: Computer-Aided Diagnosis, 69150X (17 March 2008); https://doi.org/10.1117/12.772298

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available