Share Email Print
cover

Proceedings Paper

An observer model for quantifying panning artifacts in digital pathology
Author(s): Ali R. N. Avanaki; Kathryn S. Espig; Albert Xthona; Christian Lanciault; Tom R. L. Kimpe
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Typically, pathologists pan from one region of a slide to another, choosing areas of interest for closer inspection. Due to finite frame rate and imperfect zero-order hold reconstruction (i.e., the non-zero time to reach the target brightness after a change in pixel drive), panning in whole slide images (WSI) cause visual artifacts. It is important to study the impact of such artifacts since research suggests that 49% of navigation is conducted in low-power/overview with digital pathology (Molin et al., Histopathology 2015). In this paper, we explain what types of medical information may be harmed by panning artifacts, propose a method to simulate panning artifacts, and design an observer model to predict the impact of panning artifacts on typical human observers’ performance in basic diagnostically relevant visual tasks. The proposed observer model is based on derivation of perceived object border maps from luminance and chrominance information and may be tuned to account for visual acuity of the human observer to be modeled. Our results suggest that increasing the contrast (e.g., using a wide gamut display) with a slow response panel may not mitigate the panning artifacts which mostly affect visual tasks involving spatial discrimination of objects (e.g., normal vs abnormal structure, cell type and spatial relationships between them, and low-power nuclear morphology), and that the panning artifacts worsen with increasing panning speed. The proposed methods may be used as building blocks in an automatic WSI quality assessment framework.

Paper Details

Date Published: 10 March 2017
PDF: 8 pages
Proc. SPIE 10136, Medical Imaging 2017: Image Perception, Observer Performance, and Technology Assessment, 101360O (10 March 2017); doi: 10.1117/12.2255533
Show Author Affiliations
Ali R. N. Avanaki, Barco Healthcare (United States)
Kathryn S. Espig, Barco Healthcare (United States)
Albert Xthona, Barco Healthcare (United States)
Christian Lanciault, Oregon Health & Science Univ. (United States)
Tom R. L. Kimpe, Barco Healthcare (Belgium)


Published in SPIE Proceedings Vol. 10136:
Medical Imaging 2017: Image Perception, Observer Performance, and Technology Assessment
Matthew A. Kupinski; Robert M. Nishikawa, Editor(s)

© SPIE. Terms of Use
Back to Top