Bias in hotelling observer performance computed from finite data

Matthew A. Kupinski, Eric Clarkson, Jacob Y. Hesterman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

An observer performing a detection task analyzes an image and produces a single number, a test statistic, for that image. This test statistic represents the observers "confidence" that a signal (e.g., a tumor) is present. The linear observer that maximizes the test-statistic SNR is known as the Hotelling observer. Generally, computation of the Hotelling SNR, or Hotelling trace, requires the inverse of a large covariance matrix. Recent developments have resulted in methods for the estimation and inversion of these large covariance matrices with relatively small numbers of images. The estimation and inversion of these matrices is made possible by a covariance-matrix decomposition that splits the full covariance matrix into an average detector-noise component and a background-variability component. Because the average detector-noise component is often diagonal and/or easily estimated, a full-rank, invertible covariance matrix can be produced with few images. We have studied the bias of estimates of the Hotelling trace using this decomposition for high-detector-noise and low-detector-noise situations. In extremely low-noise situations, this covariance decomposition may result in a significant bias. We will present a theoretical evaluation of the Hotelling-trace bias, as well as extensive simulation studies.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2007
Subtitle of host publicationImage Perception, Observer Performance, and Technology Assessment
DOIs
StatePublished - Oct 15 2007
EventMedical Imaging 2007: Image Perception, Observer Performance, and Technology Assessment - San Diego, CA, United States
Duration: Feb 21 2007Feb 22 2007

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume6515
ISSN (Print)1605-7422

Other

OtherMedical Imaging 2007: Image Perception, Observer Performance, and Technology Assessment
CountryUnited States
CitySan Diego, CA
Period2/21/072/22/07

Keywords

  • Bias
  • Hotelling observer
  • Image quality

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging

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