Paper
28 February 2012 Measurements of the detectability of hepatic hypovascular metastases as a function of retinal eccentricity in CT images
Ivan Diaz, Miguel P. Eckstein, Anaïs Luyet, Pierre Bize, François O. Bochud
Author Affiliations +
Abstract
The great amount of slices in volumetric data sets and limited time prevents human observers from exhaustively pointing their high resolution processing fovea to all regions in the images. Thus, many image-regions are processed with nonfoveal peripheral visual processing. Yet, most studies quantifying human detectability of signals in computer simulated textures and medical image backgrounds, have measured performance without consideration of the location of the signal in the observer's eye relative to the fovea (retinal eccentricity). Here, we measure human observer detectability of signals in CT images as a function of retinal eccentricity. A representative signal was extracted from a liver image and was added to healthy liver backgrounds at random positions. The retinal eccentricities of the signal were manipulated by varying the position of the point at which observers fixated with their eyes. Real-time video-based eye tracking was used to ensure steady fixation. High contrast fiduciary marks indicated the only possible location of the signal which was present in 50% of the images. Single CT slices were presented for 200 ms or 1 second. The observer was instructed to decide whether the image contained a signal (yes/no task). We probed 6 eccentricities with 420 decision trials per eccentricity. We found a large detectability degradation with retinal eccentricity with d' degrading by 50% at an eccentricity of 9 degrees for a 200 ms display time.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ivan Diaz, Miguel P. Eckstein, Anaïs Luyet, Pierre Bize, and François O. Bochud "Measurements of the detectability of hepatic hypovascular metastases as a function of retinal eccentricity in CT images", Proc. SPIE 8318, Medical Imaging 2012: Image Perception, Observer Performance, and Technology Assessment, 83180J (28 February 2012); https://doi.org/10.1117/12.913292
Lens.org Logo
CITATIONS
Cited by 4 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Signal detection

Liver

Computed tomography

Image processing

Eye

Medical imaging

Visual process modeling

RELATED CONTENT

The role of extra-foveal processing in 3D imaging
Proceedings of SPIE (March 10 2017)
Algorithms For Radius Of Curvature Computation.
Proceedings of SPIE (April 14 1989)
Learned saliency transformations for gaze guidance
Proceedings of SPIE (February 02 2011)

Back to Top