ABSTRACT
Breast cancer is one of the major causes of death among women.
Small clusters of micro calcifications appearing as collection of
white spots on mammograms show an early warning of breast
cancer. Early detection performed on X-ray mammography is the
key to improve breast cancer diagnosis. In order to increase
radiologist’s diagnostic performance, several computer-aided
diagnosis (CAD) schemes have been developed to improve the
detection of primary identification of this disease. In this paper, an
attempt is made to develop an adaptive k-means clustering
algorithm for breast image segmentation for the detection of micro
calcifications and also a computer based decision system for early
detection of breast cancer. The method was tested over several
images of image databases taken from BSR APPOLO for cancer
research and diagnosis, India. The algorithm works faster so that
any radiologist can take a clear decision about the appearance of
micro calcifications by visual inspection of digital mammograms
and detection accuracy has also improved as compared to some
existing works.
Keywords
K-mean;, breast image; segmentation; detection; CAD.
1. INTRODUCTION
One in eight deaths worldwide is due to cancer. Cancer is the
second leading cause of death in developed countries and the third
leading cause of death in developing countries. In 2009, about
562,340 Americans died of cancer, more than 1,500 people a day.
Approximately 1,479,350 new cancer cases were diagnosed in
2009. In the United Sates, cancer is the second most common
cause of death, and accounts for nearly 1 of every 4 deaths [1]. The
chance of developing invasive breast cancer at some time in a
woman’s life is about 1 in 8 (12%) [2]. Breast cancer continues to
be a significant public health problem in the world. Approximately
182,000 new cases of breast cancer are diagnosed and 46,000
women die of breast cancer each year in the United States [3].
Thus, the incidence and mortality of breast cancer are very high, so
much so that breast cancer is the second leading cause of cancer
death in women. The chance that breast cancer will be responsible
for a woman’s death is about 1 in 35 (about 3%) [2]. In 2009,
about 40,610 women died from breast cancer in the United States
[4]. Although breast cancer has very high incidence and death rate,
the cause of breast cancer is still unknown. No effective way to
prevent the occurrence of breast cancer exists. Although breast
cancer has very high incidence and death rate, the cause of breast
cancer is still unknown [1]. No effective way to prevent the
occurrence of breast cancer exists. Therefore, early detection is the
first crucial step towards treating breast cancer. It plays a key role
in breast cancer diagnosis and treatment. This process requires
image segmentation and analysis of the images. Based on the
analysis, detection of breast cancer along with location of affected
area is identified.

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