Clustering and pattern classification

Atam P. Dhawan, Shuangshuang Dai

Research output: Chapter in Book/Report/Conference proceedingChapter

6 Scopus citations

Abstract

Clustering is a method to arrange data points into groups or clusters based on a predefined similarity criterion. Classification maps the data points or their representative features into predefined classes to help the interpretation of the input data. There are several methods available for clustering and classification for computeraided diagnostic or decision making systems for medical applications. This chapter reviews some of the clustering and classification methods using deterministic as well as fuzzy approaches for data analysis.

Original languageEnglish (US)
Title of host publicationPrinciples and Advanced Methods in Medical Imaging and Image Analysis
PublisherWorld Scientific Publishing Co.
Pages229-266
Number of pages38
ISBN (Electronic)9789812814807
ISBN (Print)9789812705341
DOIs
StatePublished - Jan 1 2008

All Science Journal Classification (ASJC) codes

  • Medicine(all)

Fingerprint

Dive into the research topics of 'Clustering and pattern classification'. Together they form a unique fingerprint.

Cite this