A survey on enhancing mammogram image saradha arumugam academia
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A Survey on Enhancing Mammogram Image
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Recent Science: International Journal of Cancer Research, ISSN:2051-784X, Vol.46, Issue.2 466
A Survey on Enhancing Mammogram Image
T.A.Sangeetha,M.Sc.,M.Phil., (PhD).,
Assistant Professor in CS,
Kongu Arts and Science College, Erode
(Research Scholar-Mother Teresa Women’s University),
Kodaikkanal, TN,India
E-Mail:tasangeetha1979@rediffmail.com.
Dr.A.Saradha
Associate Professor & H.O.D of CSE
Institute of Road and Technology,
Erode, TN, India
E-Mail: saradha@irttech.ac.in
ABSTRACT
One of the life-threatening diseases is breast cancer and it
refers to the malignancies that grow in breasts. It is the
most common type of cancer among middle aged women.
Even though, there is no guaranteed approach to prevent
breast cancer, premature detection is the key to develop
breast cancer treatment. Mammography is one of the most
successful diagnostic techniques for premature breast
cancer detection. It is a primary imaging technique for
identification and treatment of breast cancer. On the other
hand, in general the contrast of a mammogram image is
very low and it is affected with noises, in particular for
dense and glandular tissues. In these cases the radiologist
possibly will miss certain diagnostically significant
microcalcifications. With the purpose of improving
diagnosis of cancer accurately at the premature stage,
image enhancement technology is often used which assist
in enhancing the image. Being the fact that these
mammograms are low contrast, blur and fuzzy, it is
extremely complicated to identify the microcalcifications.
Mammogram enhancement is necessary for the
enhancement of contrast features and to remove noise.
Proper image enhancement technique improves the
visibility of microcalcifications. The fundamental
requirement in mammogram enhancement is to enhance
its contrast. Several numbers of studies have been carried
out with the intention of enhancing the mammogram
images which are discussed in the literature.
Keywords---Digital Mammogram, Breast Cancer, Image
Enhancement, Microcalcifications, Contrast
Enhancement.
1. INTRODUCTION
A malignant tumor developed from breast cells is called
breast cancer. It is one of the most fatal diseases for
middle-aged women and it is one of the leading causes of
women mortality. One among eight women is affected
with this disease[1]. Premature detection is the best
possible way to improve breast cancer diagnosis because
the causes of the disease are still indefinite. Premature
detection is the key solution for improving breast cancer
diagnosis.
tumors like microcalcifications, masses and stellate
lesions [2]. Based on the medical perspective, the most
primitive symptom of breast cancer is the emergence of
microcalcifications. As a result, the detection of
microcalcification is a major part of diagnosis in early
stage breast cancer. On the other hand, microcalcification
is extremely small to identify. Mammography is known as
the best modality to identify microcalcification [3].
The tiny size of microcalcification results in unclear
visualization in mammograms. As a result, to provide the
enhanced visibility of breast cancer to physicians in
addition to automatic breast-cancer detection systems,
mammogram contrast should be enhanced [4]. In
mammograms, the size of microcalcification is almost
nearer to noise. In order to identify the breast cancer at
premature stage, it is necessary to reduce the noise level at
the same time enhance the microcalcification area.
In recent past, mammographic interpretation was
supported by computer-based techniques which are
exploited either as visualization tools or as estimation
devices [5].
Imaging techniques play a significant role in helping
perform digital mammogram, especially of abnormal
areas that cannot be felt but can be seen on a conventionalmammogram. Before any image-processing algorithm of
mammogram pre-processing steps are very important in
order to limit the search for abnormalities without undue
influence from background of the mammogram [6].
Image enhancement algorithms have been exploited for
the enhancement of contrast features and the removal of
noise. At first, contrast enhancement approaches have
exploited the convolution function or techniques such as
morphological, edge detection and band-pass filters [7, 8].
The enhancement approaches could be classified based on
the generalization of their parameters as global, local or
adaptive [9, 10].
The most significant objective of mammography is to
identify small, non-palpable cancers in its premature
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