NOTICE: Due to a lapse in annual appropriations, most of this website is not being updated. Learn more.
Form submissions will still be accepted but will not receive responses at this time. Sections of this site for programs using non-appropriated funds (such as NVLAP) or those that are excepted from the shutdown (such as CHIPS and NVD) will continue to be updated.
An official website of the United States government
Here’s how you know
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
Secure .gov websites use HTTPS
A lock (
) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.
An Automated Method for Locating Phantom Nodules in Anthropomorphic Thoracic Phantom CT Studies
Published
Author(s)
Adele P. Peskin, Alden A. Dima, Ganesh Saiprasad
Abstract
The Cancer Imaging Archive (TCIA) has a publically available FDA database consisting of just over thousand CT scans intended for facilitating the assessment of lung nodule size estimation methodologies, the development of image analysis software, as well as a wide range of different analyses. The use of these scans would be greatly facilitated by the availability of phantom nodule location data that could be input into methods that require them. This paper outlines a new image processing method to locate the phantom nodules in these CT scans in order to supplant manual location prior to their use. We present a method for extracting the phantom nodules, which involves phantom lung wall removal and separation of the phantom nodules from surrounding phantom blood vessels. Nodule locations are described by rectangular boxes bounding their positions in the scans and volume estimations.
Proceedings Title
Proceedings of the 2012 International Conference on Image Processing, Computer Vision, & Pattern Recognition, IPCV 2012
Peskin, A.
, Dima, A.
and Saiprasad, G.
(2012),
An Automated Method for Locating Phantom Nodules in Anthropomorphic Thoracic Phantom CT Studies, Proceedings of the 2012 International Conference on Image Processing, Computer Vision, & Pattern Recognition, IPCV 2012, Las Vegas, NV
(Accessed October 8, 2025)