Abstract
It is generally well known that the appearance of breast tissue in a mammogram is considerably more complex in a statistical sense than a simple random Gaussian texture, even when the correlation structure of the Gaussian has been set to match the power-law power spectrum of mammograms. However there has not been a systematic way to characterize the extent of departure from a Gaussian process. We address this topic here by proposing a noisy-Laplacian distribution to model response histograms derived from digital (or digitized) mammograms. We describe the distribution in terms of the probability density function and cumulative density function, as well as moments up to fourth order. We also demonstrate the usefulness of the new distribution by fitting it to responses from digital mammography.
Original language | English (US) |
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Title of host publication | Progress in Biomedical Optics and Imaging - Proceedings of SPIE |
Volume | 7966 |
DOIs | |
State | Published - 2011 |
Event | Medical Imaging 2011: Image Perception, Observer Performance, and Technology Assessment - Lake Buena Vista, FL, United States Duration: Feb 16 2011 → Feb 17 2011 |
Other
Other | Medical Imaging 2011: Image Perception, Observer Performance, and Technology Assessment |
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Country/Territory | United States |
City | Lake Buena Vista, FL |
Period | 2/16/11 → 2/17/11 |
Keywords
- Gabor filters
- Image structure
- Non-Gaussian image statistics
- Scene statistics
ASJC Scopus subject areas
- Atomic and Molecular Physics, and Optics
- Electronic, Optical and Magnetic Materials
- Biomaterials
- Radiology Nuclear Medicine and imaging