no code implementations • 30 Jun 2015 • Ali R. N. Avanaki, Kathryn S. Espig, Tom R. L. Kimpe, Andrew D. A. Maidment
By analyzing human readers' performance in detecting small round lesions in simulated digital breast tomosynthesis background in a location known exactly scenario, we have developed a model observer that is a better predictor of human performance with different levels of background complexity (i. e., anatomical and quantum noise).
no code implementations • 30 Jun 2015 • Ali R. N. Avanaki, Kathryn S. Espig, Sameer Sawhney, Liron Pantanowitz, Anil V. Parwani, Albert Xthona, Tom R. L. Kimpe
The effect of display aging using these display models and images is further analyzed through a human reader study designed to quantify the effects from a clinical perspective.
no code implementations • 5 Aug 2014 • Ali R. N. Avanaki, Kathryn S. Espig, Albert Xthona, Tom R. L. Kimpe, Predrag R. Bakic, Andrew D. A. Maidment
Within the framework of a virtual clinical trial for breast imaging, we aim to develop numerical observers that follow the same detection performance trends as those of a typical human observer.
no code implementations • 24 Mar 2014 • Ali R. N. Avanaki, Kathryn S. Espig, Andrew D. A. Maidment, Cedric Marchessoux, Predrag R. Bakic, Tom R. L. Kimpe
The probability p is considered to be equal to the perceived amplitude of the frequency component and thus can be used by a traditional model observer (e. g., LG-msCHO) in the space-time domain.