Masters Theses

Varun Shah

Abstract

"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.

Advisor(s)

Lee, Hyoung-Koo
Moss, Randy Hays, 1953-

Committee Member(s)

Stanley, R. Joe

Department(s)

Electrical and Computer Engineering

Degree Name

M.S. in Electrical Engineering

Publisher

Missouri University of Science and Technology

Publication Date

Fall 2012

Pagination

x, 51 pages

Note about bibliography

Includes bibliographical references (pages 39-41).

Rights

© 2012 Varun Shah, All rights reserved.

Document Type

Thesis - Open Access

File Type

text

Language

English

Subject Headings

Breast -- Radiography
Image processing -- Digital techniques -- Mathematical models
Wavelets (Mathematics)

Thesis Number

T 10127

Print OCLC #

841806183

Electronic OCLC #

807987504

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