Modeling human visual detection of low-contrast objects in fluoroscopy image sequences

David L. Wilson; Kadri N. Jabri; Ping Xue

doi:10.1117/12.271301

16 April 1997 Modeling human visual detection of low-contrast objects in fluoroscopy image sequences

David L. Wilson, Kadri N. Jabri, Ping Xue

Proceedings Volume 3036, Medical Imaging 1997: Image Perception; (1997) https://doi.org/10.1117/12.271301
Event: Medical Imaging 1997, 1997, Newport Beach, CA, United States

Abstract

We have performed a large variety of perception experiments aimed at issues in x-ray fluoroscopy. These include effects of image acquisition rate, digital temporal filtering, motion, and x-ray system motion blur. In this report, two model structures were considered. Both were non-prewhitening matched filter models modified to include a spatio-temporal visual system contrast sensitivity function. The first model used a spatial template following temporal integration and the second used a spatio-temporal template. The first model best described all data. However, it did not describe all motion experiments as accurately as the second. Our conclusion was that given an experiment, we should use the simplest model which most accurately describes similar experiments. Models will help plan critical experiments, allow one to concisely describe results, and predict similar experiments. Both models will be used to further our ultimate goal of using quantitative image quality studies to minimize dose and maximize image quality in x-ray fluoroscopy.

Citation Download Citation

David L. Wilson, Kadri N. Jabri, and Ping Xue "Modeling human visual detection of low-contrast objects in fluoroscopy image sequences", Proc. SPIE 3036, Medical Imaging 1997: Image Perception, (16 April 1997); https://doi.org/10.1117/12.271301

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