A study of digital mammograms by using clustering algorithms

S. M. Halawani; M. Alhaddad; A. Ahmad

A study of digital mammograms by using clustering algorithms

S. M. Halawani, M. Alhaddad, A. Ahmad

Research output: Contribution to journal › Article › peer-review

Abstract

This study presents clustering algorithms to study digital mammograms. Probabilistic clustering algorithms performed better than hierarchical clustering algorithm. Clustering results are competitive with classification results, indicating that clustering algorithms can be used as an important tool to study digital mammograms. Probabilistic clustering algorithms can also be used by radiologists to improve their prediction accuracy.

Original language	English
Pages (from-to)	594-600
Number of pages	7
Journal	Journal of Scientific and Industrial Research
Volume	71
Issue number	9
Publication status	Published - Sept 2012
Externally published	Yes

Keywords

Classification
Clustering
K-mean clustering
Mammograms
Mixed datasets
Probabilistic

ASJC Scopus subject areas

General

Cite this

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title = "A study of digital mammograms by using clustering algorithms",

abstract = "This study presents clustering algorithms to study digital mammograms. Probabilistic clustering algorithms performed better than hierarchical clustering algorithm. Clustering results are competitive with classification results, indicating that clustering algorithms can be used as an important tool to study digital mammograms. Probabilistic clustering algorithms can also be used by radiologists to improve their prediction accuracy.",

keywords = "Classification, Clustering, K-mean clustering, Mammograms, Mixed datasets, Probabilistic",

author = "Halawani, {S. M.} and M. Alhaddad and A. Ahmad",

year = "2012",

month = sep,

language = "English",

volume = "71",

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journal = "Journal of Scientific and Industrial Research",

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AU - Alhaddad, M.

AU - Ahmad, A.

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N2 - This study presents clustering algorithms to study digital mammograms. Probabilistic clustering algorithms performed better than hierarchical clustering algorithm. Clustering results are competitive with classification results, indicating that clustering algorithms can be used as an important tool to study digital mammograms. Probabilistic clustering algorithms can also be used by radiologists to improve their prediction accuracy.

AB - This study presents clustering algorithms to study digital mammograms. Probabilistic clustering algorithms performed better than hierarchical clustering algorithm. Clustering results are competitive with classification results, indicating that clustering algorithms can be used as an important tool to study digital mammograms. Probabilistic clustering algorithms can also be used by radiologists to improve their prediction accuracy.

KW - Classification

KW - Clustering

KW - K-mean clustering

KW - Mammograms

KW - Mixed datasets

KW - Probabilistic

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A study of digital mammograms by using clustering algorithms

Abstract

Keywords

ASJC Scopus subject areas

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