Adaptive thresholding of chest temporal subtraction images in computer-aided diagnosis of pathologic change

Melanie Harrison; Jared Looper; Samuel G. Armato III

doi:10.1117/12.2217177

24 March 2016 Adaptive thresholding of chest temporal subtraction images in computer-aided diagnosis of pathologic change

Melanie Harrison, Jared Looper, Samuel G. Armato III

Author Affiliations +

Proceedings Volume 9785, Medical Imaging 2016: Computer-Aided Diagnosis; 978536 (2016) https://doi.org/10.1117/12.2217177
Event: SPIE Medical Imaging, 2016, San Diego, California, United States

Abstract

Radiologists frequently use chest radiographs acquired at different times to diagnose a patient by identifying regions of change. Temporal subtraction (TS) images are formed when a computer warps a radiographic image to register and then subtract one image from the other, accentuating regions of change. The purpose of this study was to create a computeraided diagnostic (CAD) system to threshold chest TS images and identify candidate regions of pathologic change. Each thresholding technique created two different candidate regions: light and dark. Light regions have a high gray-level mean, while dark regions have a low gray-level mean; areas with no change appear as medium-gray pixels. Ten different thresholding techniques were examined and compared. By thresholding light and dark candidate regions separately, the number of properly thresholded regions improved. The thresholding of light and dark regions separately produced fewer overall candidate regions that included more regions of actual pathologic change than global thresholding of the image. Overall, the moment-preserving method produced the best results for light regions, while the normal distribution method produced the best results for dark regions. Separation of light and dark candidate regions by thresholding shows potential as the first step in creating a CAD system to detect pathologic change in chest TS images.

Citation Download Citation

Melanie Harrison, Jared Looper, and Samuel G. Armato III "Adaptive thresholding of chest temporal subtraction images in computer-aided diagnosis of pathologic change", Proc. SPIE 9785, Medical Imaging 2016: Computer-Aided Diagnosis, 978536 (24 March 2016); https://doi.org/10.1117/12.2217177

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