GVIP Journal    

ICGST

Issue(5)

GVIP
Automatic Detection of Microcalcification in Mammograms – A Review
 
K.Thangavel (1), M.Karnan (2), R.Sivakumar (3), A. Kaja Mohideen (3)
1: Department of Mathematics, Gandhigram Rural Institute-Deemed University,
2: Department of computer science, Gandhigram Rural Institute-Deemed University,
Gandhigram-624302, Tamil Nadu, India. Email: karnanme@yahoo.com fax:91-4551-227229
3: Department of Computer Science and Engineering, R.V.S.College of Engineering & Technology, Dindigul, Tamil Nadu, India.
 
Abstract:
In this review paper, it is intended to summarize and compare the methods of automatic detection of microcalcifications in digitized mammograms used in various stages of the Computer Aided Detection systems (CAD). In particular, the pre processing and enhancement, bilateral subtraction techniques, segmentation algorithms, feature extraction, selection and classification, classifiers, Receiver Operating Characteristic (ROC); Free-response Receiver Operating Characteristic (FROC) analysis and their performances are studied and compared.
 
Keywords: Mammography, Microcalcification, Image Enhancement, Segmentation, Feature extraction.
 
Biography:
 
THANGAVEL KUTTIANNAN, received the Master of Science from Department of Mathematics, Bharathidasan University in 1986, and Master of Computer Applications Degree from Madurai Kamaraj University, India in 2001. He got his Ph. D. Degree from Mathematics department, Gandhigram Rural Institute-Deemed University in 1999. Currently he is working as Reader in Mathematics Department, Gandhigram Rural Institute-Deemed University, and his experience started from 1988; His area of interests includes medical image processing, artificial intelligence, neural network, and fuzzy logic.
KARNAN MARCUS, received the Master of Computer Science and Engineering Degree from Computer Science and Engineering Department, from Government College of Engineering, Manonmaniam Sundaranar University, Tamil Nadu, India, in 2000. Currently he is working as Assistant Professor, Department of Computer Science & Engineering Department, RVS College of Engineering & Technology, Tamil Nadu, India. And doing part-time research in the Department of computer Science and Applications, Gandhigram Rural Institute-Deemed University, Tamil Nadu, India. His area of interests includes medical image processing, artificial intelligence, neural network, genetic algorithm, pattern recognition and fuzzy logic.
 
SIVA KUMAR RAMAKRISHNAN,. Received the Master of Computer Science and Engineering Degree from Computer Science and Engineering Department, from Government College of Engineering, Manonmaniam Sundaranar University, Tamil Nadu, India, in 2000. Currently he is working as Assistant Professor, Department of Computer Science & Engineering, RVS College of Engineering & Technology, Tamil Nadu, India. His area of interests includes medical image processing, artificial intelligence, neural network, and fuzzy logic.
KAJA MOHIDEEN ABUBAKKER, received the Master of Computer Applications Degree from Computer Science Department, Bharathidasan University, Tamil Nadu, India, in 2000. Currently he is working as Research Assistant, in Department of Computer Science & Engineering RVS College of Engineering & Technology, Tamil Nadu, India. His area of interests includes medical image processing, artificial intelligence, and neural network.

The following author designated as corresponding author:

Karnan Marcus,

E-mail id: karnanme@yahoo.com, rsk_siva@mailcity.com, ktvel@rediffmail.com
Postal Address: 153, Palayam, Palani, Dindigul Dt, Tamil Nadu, India – 624601.
Fax.No:91-4551-227229,91-4551-227230,
Telephone.No:91-4551-227229,91-4551-2272.

BibTex:

@ARTICLE{P1150518001,

AUTHOR = {K.Thangavel and M.Karnan and R.Sivakumar and A. Kaja Mohideen},

TITLE = {Automatic Detection of Microcalcification in Mammograms – A Review},

JOURNAL = {ICGST International Journal on Graphics, Vision and Image Processing, GVIP},

YEAR = {2005},

MONTH = {May},

VOLUME = {05},

ISSUE={5},

PAGES = {31--61}

}

( Full Paper 1.00 MB)