Breast cancer is the most commonly diagnosed cancer and the second leading cause of cancer deaths among American women today. Despite many advances in cancer treatment and prevention, early detection of breast cancer remains the best opportunity for effective treatment and low mortality. Conventional x-ray mammography has been the gold standard for breast imaging for many years, and has been shown to reduce mortality due to breast cancer. However, there remains about a 30 percent lesion miss rate using conventional mammography, delaying detection and treatment for a significant number of women. Digital mammography offers the potential for significant improvements in diagnostic efficiency and accuracy, but as with any new imaging technology, a great deal of work is needed to optimize design and operating parameters in various components of the imaging chain. One extremely important link in the digital mammography chain is the display. Although there are a number of interesting display media on the horizon (e.g., liquid crystal displays, field emission displays), the most common, widely available and inexpensive display is the cathode ray tube (CRT) monitor. However, there is still much work to be done to optimize the CRT monitor for display of digital mammograms. This program's goal is to develop an efficient method of optimizing display performance for digital mammography systems. We will address three aspects of the "Development of Digital Mammography Displays and Workstations" PA (PA-99-082): (1) predictive models, (2) perception and (3) workstation (display) design. In particular, radiologist performance will be measures for several display characteristics. These results will then be used to enhance and validate a model of human visual performance (JNDmetrix Vision Model). The JND metrix model will then be used to systematically explore and optimize CRT design tradeoffs for current and future digital-mammography display systems.
|Effective start/end date||9/1/00 → 5/31/05|
- National Institutes of Health: $415,565.00
- Biochemistry, Genetics and Molecular Biology(all)