Full Content is available to subscribers

Subscribe/Learn More  >
Proceedings Article

Optimizing imaging hardware for estimation tasks

[+] Author Affiliations
Matthew A. Kupinski, Eric Clarkson

Optical Sciences Ctr./Univ. of Arizona (USA) and Univ. of Arizona (USA)

Kevin Gross

Optical Sciences Ctr./Univ. of Arizona (USA)

John W. Hoppin

Univ. of Arizona (USA)

Proc. SPIE 5034, Medical Imaging 2003: Image Perception, Observer Performance, and Technology Assessment, 309 (May 21, 2003); doi:10.1117/12.480337
Text Size: A A A
From Conference Volume 5034

  • Medical Imaging 2003: Image Perception, Observer Performance, and Technology Assessment
  • Dev P. Chakraborty; Elizabeth A. Krupinski
  • San Diego, CA | February 15, 2003

abstract

Medical imaging is often performed for the purpose of estimating a clinically relevant parameter. For example, cardiologists are interested in the cardiac ejection fraction, the fraction of blood pumped out of the left ventricle at the end of each heart cycle. Even when the primary task of the imaging system is tumor detection, physicians frequently want to estimate parameters of the tumor, e.g. size and location. For signal-detection tasks, we advocate that the performance of an ideal observer be employed as the figure of merit for optimizing medical imaging hardware. We have examined the use of the minimum variance of the ideal, unbiased estimator as a figure of merit for hardware optimization. The minimum variance of the ideal, unbiased estimator can be calculated using the Fisher information matrix. To account for both image noise and object variability, we used a statistical method known as Markov-chain Monte Carlo. We employed a lumpy object model and simulated imaging systems to compute our figures of merit. We have demonstrated the use of this method in comparing imaging systems for estimation tasks.

© (2003) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
Citation

Matthew A. Kupinski ; Eric Clarkson ; Kevin Gross and John W. Hoppin
"Optimizing imaging hardware for estimation tasks", Proc. SPIE 5034, Medical Imaging 2003: Image Perception, Observer Performance, and Technology Assessment, 309 (May 21, 2003); doi:10.1117/12.480337; http://dx.doi.org/10.1117/12.480337


Access This Proceeding
Sign in or Create a personal account to Buy this proceeding ($15 for members, $18 for non-members).

Figures

Tables

NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

Advertisement

 

 

  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Proceeding
Sign in or Create a personal account to Buy this proceeding ($15 for members, $18 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.