Automatic lung nodule detection in thick slice CT: a comparative study of different gating schemes in CAD

Pandu Devarakota; M. S. Dinesh; Pragnya Maduskar; Siddharth Vikal; Laks Raghupathi; Marcos Salganicoff

doi:10.1117/12.878404

4 March 2011 Automatic lung nodule detection in thick slice CT: a comparative study of different gating schemes in CAD

Pandu Devarakota, M. S. Dinesh, Pragnya Maduskar, Siddharth Vikal, Laks Raghupathi, Marcos Salganicoff

Proceedings Volume 7963, Medical Imaging 2011: Computer-Aided Diagnosis; 79630E (2011) https://doi.org/10.1117/12.878404
Event: SPIE Medical Imaging, 2011, Lake Buena Vista (Orlando), Florida, United States

Abstract

Common chest CT clinical workflows for detecting lung nodules use a large slice thickness protocol (typically 5 mm). However, most existing CAD studies are performed on a thin slice data (0.3-2 mm) available on state-of-the art scanners. A major challenge for the widespread clinical use of Lung CAD is the concurrent availability of both thick and thin resolutions for use by radiologist and CAD respectively. Having both slice thickness reconstructions is not always possible based on the availability of scanner technologies, acquisition parameters chosen at remote site, and transmission and archiving constraints that may make transmission and storage of large data impracticable. However, applying current thin-slice CAD algorithms on thick slice cases outside their designed acquisition parameters may result in degradation of sensitivity and high false-positive rate making them clinically unacceptable. Therefore a CAD system that can handle thicker slice acquisitions is desirable to address those situations. In this paper, we propose a CAD system which works directly on thick slice scans. We first propose a multi-stage classifier based CAD system for detecting lung nodules in such data. Furthermore, we propose different gating systems adapted for thick slice scans. The proposed gating schemes are based on: 1. wall-attached and non wall-attached. 2. central and non-central region. These gating schemes can be used independently or combined as well. Finally, we present prototype¹ results showing significant improvement of CAD sensitivity at much better false positive rate on thick-slice CT images are presented.

Citation Download Citation

Pandu Devarakota, M. S. Dinesh, Pragnya Maduskar, Siddharth Vikal, Laks Raghupathi, and Marcos Salganicoff "Automatic lung nodule detection in thick slice CT: a comparative study of different gating schemes in CAD", Proc. SPIE 7963, Medical Imaging 2011: Computer-Aided Diagnosis, 79630E (4 March 2011); https://doi.org/10.1117/12.878404

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

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
8 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Lung

Computer aided diagnosis and therapy

CAD systems

Computer aided design

Computed tomography

Data storage

Feature extraction

Show All Keywords

Keywords/Phrases

Search In:

Publication Years