Abstract
The detectability of low-contrast lesions in medical images can be affected significantly by the choice of grayscale window width and level (W/L) for electronic display. Our objective was to measure the effects of various W/L conditions on lesion detectability in simulated and real mammographic images, and then correlate observer performance with predictions of detection thresholds derived from a visual discrimination model (VDM). In the first experiment, detection thresholds were measured in 2AFC trials for five W/L conditions applied to simulated mammographic backgrounds and lesions (i.e., Gaussian "masses" and blurred-disk "microcalcification clusters") using nonmedical observers. In the second experiment, the detectability of real microcalcification clusters in digitized mammograms was evaluated for three W/L conditions in an ROC observer study with mammographers. For the simulated images, there was generally good agreement between model and experimental thresholds and their variations across W/L conditions. Both experimental and model results showed significant reductions in thresholds when W/L processing was applied locally near the lesion. ROC results with digitized mammograms read by radiologists, however, failed to show enhanced detection of microcalcifications using a localized W/L frame, probably due to the nonuniform appearance of parenchymal tissue across the image.
Original language | English (US) |
---|---|
Pages (from-to) | 462-473 |
Number of pages | 12 |
Journal | Proceedings of SPIE - The International Society for Optical Engineering |
Volume | 5034 |
DOIs | |
State | Published - 2003 |
Event | Medical Imaging 2003: Image Perception, Observer Performance, and Technology Assessment - San Diego, CA, United States Duration: Feb 18 2003 → Feb 20 2003 |
Keywords
- Grayscale window/level
- Lesion detection
- Mammography
- Observer performance
- Visual discrimination model
ASJC Scopus subject areas
- Electronic, Optical and Magnetic Materials
- Condensed Matter Physics
- Computer Science Applications
- Applied Mathematics
- Electrical and Electronic Engineering