Early Stage Detection of Microcalcifications in Mammograms: A Survey
Breast cancer is one of the most deadly diseases for women. Mammography is the most effective method for the
early stage detection of breast diseases. Survival rate of breast cancer is approaches 100 percent, if cancer is detected early
by using breast self examination (BSE) and clinical breast examination (CBE) at the aged of 40-49 years. Mammography
continues to be regarded as a very useful diagnostic tool for detection & diagnosis of breast lesions, it uses lower levels of
radiation than ordinary chest x-rays. But, a meta analysis is showed that the sensitivity of screening mammography ranged
from 83% to 95 %.with a false positive rate of 0.9% to 6.5 % respectively. The appropriate method used for early detection
of pre-cancerous symptoms is screening mammography, which has to be conducted as a regular test for women.
Calcification clusters are said to be an early sign of breast cancer. Microcalcifications are very small bits of calcium deposits
present inside the breast tissue. Many researchers have proposed the algorithm for Micro calcification detection based on
wavelet transform, mathematical morphology and neural networks.CAD system is also used for automatic detection of
clustered micro calcifications in digitized mammograms. This paper is review of detection of micro calcification in
mammograms using wavelet.
Keywords— Mammograms, Microcalcification, BSE, CBE, CAD.