### Abstract

We extend a method for linear template estimation developed by Abbey et al. which demonstrated that a linear observer template can be estimated effectively through a two-alternative forced choice (2AFC) experiment, assuming the noise in the images is Gaussian, or multivariate normal (MVN). We relax this assumption, allowing the noise in the images to be drawn from a weighted sum of MVN distributions, which we call a multi-peaked MVN (MPMVN) distribution. Our motivation is that more complicated probability density functions might be approximated in general by such MPMVN distributions. Our extension of Abbey et al.'s method requires us to impose the additional constraint that the covariance matrices of the component peaks of the signal-present noise distribution all be equal, and that the covariance matrices of the component peaks of the signal-absent noise distribution all be equal (but different in general from the signal-present covariance matrices). Preliminary research shows that our generalized method is capable of producing unbiased estimates of linear observer templates in the presence of MPMVN noise under the stated assumptions. We believe this extension represents a next step toward the general treatment of arbitrary image noise distributions.

Original language | English (US) |
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Title of host publication | Proceedings of SPIE - The International Society for Optical Engineering |

Publisher | Society of Photo-Optical Instrumentation Engineers |

Pages | 85-96 |

Number of pages | 12 |

Volume | 3981 |

State | Published - 2000 |

Externally published | Yes |

Event | Medical Imaging 2000: Image Perception and Performance - San Diego, CA, USA Duration: Feb 16 2000 → Feb 17 2000 |

### Other

Other | Medical Imaging 2000: Image Perception and Performance |
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City | San Diego, CA, USA |

Period | 2/16/00 → 2/17/00 |

### Fingerprint

### ASJC Scopus subject areas

- Electrical and Electronic Engineering
- Condensed Matter Physics

### Cite this

*Proceedings of SPIE - The International Society for Optical Engineering*(Vol. 3981, pp. 85-96). Society of Photo-Optical Instrumentation Engineers.

**Estimation of linear observer templates in the presence of multi-peaked Gaussian noise through 2AFC experiments.** / Edwards, Darrin C.; Kupinski, Matthew A; Nishikawa, Robert M.; Metz, Charles E.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Proceedings of SPIE - The International Society for Optical Engineering.*vol. 3981, Society of Photo-Optical Instrumentation Engineers, pp. 85-96, Medical Imaging 2000: Image Perception and Performance, San Diego, CA, USA, 2/16/00.

}

TY - GEN

T1 - Estimation of linear observer templates in the presence of multi-peaked Gaussian noise through 2AFC experiments

AU - Edwards, Darrin C.

AU - Kupinski, Matthew A

AU - Nishikawa, Robert M.

AU - Metz, Charles E.

PY - 2000

Y1 - 2000

N2 - We extend a method for linear template estimation developed by Abbey et al. which demonstrated that a linear observer template can be estimated effectively through a two-alternative forced choice (2AFC) experiment, assuming the noise in the images is Gaussian, or multivariate normal (MVN). We relax this assumption, allowing the noise in the images to be drawn from a weighted sum of MVN distributions, which we call a multi-peaked MVN (MPMVN) distribution. Our motivation is that more complicated probability density functions might be approximated in general by such MPMVN distributions. Our extension of Abbey et al.'s method requires us to impose the additional constraint that the covariance matrices of the component peaks of the signal-present noise distribution all be equal, and that the covariance matrices of the component peaks of the signal-absent noise distribution all be equal (but different in general from the signal-present covariance matrices). Preliminary research shows that our generalized method is capable of producing unbiased estimates of linear observer templates in the presence of MPMVN noise under the stated assumptions. We believe this extension represents a next step toward the general treatment of arbitrary image noise distributions.

AB - We extend a method for linear template estimation developed by Abbey et al. which demonstrated that a linear observer template can be estimated effectively through a two-alternative forced choice (2AFC) experiment, assuming the noise in the images is Gaussian, or multivariate normal (MVN). We relax this assumption, allowing the noise in the images to be drawn from a weighted sum of MVN distributions, which we call a multi-peaked MVN (MPMVN) distribution. Our motivation is that more complicated probability density functions might be approximated in general by such MPMVN distributions. Our extension of Abbey et al.'s method requires us to impose the additional constraint that the covariance matrices of the component peaks of the signal-present noise distribution all be equal, and that the covariance matrices of the component peaks of the signal-absent noise distribution all be equal (but different in general from the signal-present covariance matrices). Preliminary research shows that our generalized method is capable of producing unbiased estimates of linear observer templates in the presence of MPMVN noise under the stated assumptions. We believe this extension represents a next step toward the general treatment of arbitrary image noise distributions.

UR - http://www.scopus.com/inward/record.url?scp=0033741095&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0033741095&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0033741095

VL - 3981

SP - 85

EP - 96

BT - Proceedings of SPIE - The International Society for Optical Engineering

PB - Society of Photo-Optical Instrumentation Engineers

ER -