Share Email Print

Proceedings Paper

Perception-driven IT-CADe analysis for the detection of masses in screening mammography: initial investigation
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

We have previously reported an interactive information-theoretic CADe (IT-CADe) system for the detection of masses in screening mammograms. The system operates in either traditional static mode or in interactive mode whenever the user requests a second opinion. In this study we report preliminary investigation of a new paradigm of clinical integration, guided by the user's eye-gazing and reporting patterns. An observer study was conducted in which 6 radiologists evaluated 20 mammographic cases while wearing a head-mounted eye-tracking device. For each radiologistreported location, eye-gazing data were collected. Image locations that attracted prolonged dwelling (>1000msec) but were not reported were also recorded. Fixed size regions of interest (ROIs) were extracted around all above locations and analyzed using the IT-CADe system. Preliminary analysis showed that IT-CADe correctly confirmed 100% of reported true mass locations while eliminating 12.5% of the reported false positive locations. For unreported locations that attracted long dwelling, IT-CADe identified 4/6 false negative errors (i.e., errors of decision) while overcalling 8/84 TN decisions. Finally, for missed true masses that attracted short (i.e., errors of recognition) or no dwelling at all (i.e., errors of search), IT-CADe detected 5/8 of them. These results suggest that IT-CADe customization to the user's eye-gazing and reporting pattern could potentially help delineate the various sources of diagnostic error (search, recognition, decision) for each individual user and provide targeted decision support, thus improving the human-CAD synergy.

Paper Details

Date Published: 9 March 2010
PDF: 6 pages
Proc. SPIE 7624, Medical Imaging 2010: Computer-Aided Diagnosis, 762406 (9 March 2010); doi: 10.1117/12.845495
Show Author Affiliations
Georgia D. Tourassi, Duke Univ. Medical Ctr. (United States)
Maciej A. Mazurowski, Duke Univ. Medical Ctr. (United States)
Elizabeth A. Krupinski, The Univ. of Arizona (United States)

Published in SPIE Proceedings Vol. 7624:
Medical Imaging 2010: Computer-Aided Diagnosis
Nico Karssemeijer; Ronald M. Summers, Editor(s)

© SPIE. Terms of Use
Back to Top