Model observers for complex discrimination tasks: assessments of multiple coronary stent placements

Sheng Zhang; Craig K. Abbey; Arian Teymoorian; Xiaolin Da; James S. Whiting; Miguel P. Eckstein

doi:10.1117/12.846378

3 March 2010 Model observers for complex discrimination tasks: assessments of multiple coronary stent placements

Sheng Zhang, Craig K. Abbey, Arian Teymoorian, Xiaolin Da, James S. Whiting, Miguel P. Eckstein

Proceedings Volume 7627, Medical Imaging 2010: Image Perception, Observer Performance, and Technology Assessment; 76270W (2010) https://doi.org/10.1117/12.846378
Event: SPIE Medical Imaging, 2010, San Diego, California, United States

Abstract

As an important clinical task, evaluating the placement of multiple coronary stents requires fine judgments of distance between stents. However, making these judgments is limited by low system resolution, noise, low contrast of the deployed stent, and stent motion during the cardiac cycle. We use task performance as a figure of merit for optimizing image display parameters. In previous work, we described our simulation procedure in detail, and also reported results of human observers for a visual task involving discrimination of 4 gap sizes under various frame rates and number of frames. Here, we report the results of three spatial model observers (i.e. NPW, NPWE, and PWMF) and two temporal sensitivity functions (i.e. transient and sustained) for the same task. Under signal known exactly conditions, we find that model observers can be used to predict human observers in terms of discrimination accuracy by adding internal noise.

Citation Download Citation

Sheng Zhang, Craig K. Abbey, Arian Teymoorian, Xiaolin Da, James S. Whiting, and Miguel P. Eckstein "Model observers for complex discrimination tasks: assessments of multiple coronary stent placements", Proc. SPIE 7627, Medical Imaging 2010: Image Perception, Observer Performance, and Technology Assessment, 76270W (3 March 2010); https://doi.org/10.1117/12.846378

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