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2D single-slice vs. 3D viewing of simulated tomosynthesis images of a small-scale breast tissue model
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Paper Abstract

We investigate whether humans need to be shown the entire image stack (3D) or only the central slice (2D) of the lesion of breast tomosynthesis images in signal-known-exactly detection experiments. A directional small-scale breast tissue model based on random power-law noise was used. Assuming a breast tomosynthesis geometry, the tissue volumes were projected and reconstructed forming volumes-of-interest (VOI)s. Three different sizes of spheres with blurred edges were used to simulate lesions. The spheres were added on the VOIs to represent signal-present VOIs. Signal-present and signalabsent VOIs were presented during 2-alternative forced-choice experiments to 5 human observers in two modes; (i) 3D mode, in which all slices of the VOI were repeatedly displayed in ciné mode; and in (ii) 2D mode, in which only the central slice of the reconstructed VOI (where the signal-present VOIs contained the center of the spherical lesion) was displayed using 2-alternative forced-choice experiments. Percent correct (PC) of the detection performance of all observers was evaluated. No significant differences were found systematically in the PC for the 3D and 2D image viewing for this type of backgrounds. We plan to investigate these further, along with the development of a model observer that correlates well with human performance in tomosynthesis.

Paper Details

Date Published: 4 March 2019
PDF: 7 pages
Proc. SPIE 10952, Medical Imaging 2019: Image Perception, Observer Performance, and Technology Assessment, 109520V (4 March 2019); doi: 10.1117/12.2512053
Show Author Affiliations
Christiana Balta, LRCB (Netherlands)
Radboud Univ. Medical Ctr. (Netherlands)
Ioannis Sechopoulos, LRCB (Netherlands)
Radboud Univ. Medical Ctr. (Netherlands)
Wouter J. H. Veldkamp, Leiden Univ. Medical Ctr. (Netherlands)
Ruben E. van Engen, LRCB (Netherlands)
Ingrid Reiser, Univ. of Chicago (United States)

Published in SPIE Proceedings Vol. 10952:
Medical Imaging 2019: Image Perception, Observer Performance, and Technology Assessment
Robert M. Nishikawa; Frank W. Samuelson, Editor(s)

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