"Breast cancer is one of the most common cancers and claims over one thousand lives every day. Breast cancer turns fatal only when diagnosed in late stages, but can be cured when diagnosed in its early stages. Over the last two decades, Digital Mammography has served the diagnosis of breast cancer. It is a very powerful aid for early detection of breast cancer. However, the images produced by mammography typically contain a great amount noise from the inherent characteristics of the imaging system and the radiation involved. Shot noise or quantum noise is the most significant noise which emerges as a result of uneven distribution of incident photons on the receptor. The X-ray dose given to patients must be minimized because of the risk of exposure. This noise present in mammograms manifests itself more when the dose of X-ray radiation is less and therefore needs to be treated before enhancing the mammogram for contrast and clarity. Several approaches have been taken to reduce the amount of noise in mammograms. This thesis presents a study of the wavelet-based techniques employed for noise reduction in mammograms"--Abstract, page iii.
Moss, Randy Hays, 1953-
Stanley, R. Joe
Electrical and Computer Engineering
M.S. in Electrical Engineering
Missouri University of Science and Technology
x, 51 pages
© 2012 Varun Shah, All rights reserved.
Thesis - Open Access
Breast -- Radiography
Image processing -- Digital techniques -- Mathematical models
Print OCLC #
Electronic OCLC #
Link to Catalog Record
Shah, Varun, "A study of wavelet-based noise reduction techniques in mammograms" (2012). Masters Theses. 5285.