Histograms in Breast Density Classification: Are 4 better than 1?

Izzati Muhimmah; Erika R. E. Denton; Reyer Zwiggelaar

Histograms in Breast Density Classification: Are 4 better than 1?

Izzati Muhimmah, Erika R. E. Denton, Reyer Zwiggelaar

Department of Computer Science

Research output: Contribution to conference › Paper

Abstract

Breast density is known to be an important indicator of breast cancer risk. Quantitative estimation approaches have been developed and some of these are based on grey level or texture metrics. Developing an example of the former, we combined multi-resolution histograms and pattern matching approaches. The results show good agreement compared to expert radiologist classification. The presented approach provides similar results to existing methods and limitations are discussed.

Original language	English
Number of pages	3
Publication status	Published - 18 Jun 2005
Event	Seminar Nasional Aplikasi Teknologi Informasi 2005 - , Indonesia Duration: 18 Jun 2005 → 18 Jun 2005

Seminar

Seminar	Seminar Nasional Aplikasi Teknologi Informasi 2005
Abbreviated title	SNATI 2005
Country/Territory	Indonesia
Period	18 Jun 2005 → 18 Jun 2005

Keywords

Multi-Resolution Histogram Technique
Mammography
Breast Density Classification

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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@conference{1e3530294f2c46949f98b6014f1904c8,

title = "Histograms in Breast Density Classification: Are 4 better than 1?",

abstract = "Breast density is known to be an important indicator of breast cancer risk. Quantitative estimation approaches have been developed and some of these are based on grey level or texture metrics. Developing an example of the former, we combined multi-resolution histograms and pattern matching approaches. The results show good agreement compared to expert radiologist classification. The presented approach provides similar results to existing methods and limitations are discussed.",

keywords = "Multi-Resolution Histogram Technique, Mammography, Breast Density Classification",

author = "Izzati Muhimmah and Denton, {Erika R. E.} and Reyer Zwiggelaar",

year = "2005",

month = jun,

day = "18",

language = "English",

note = "Seminar Nasional Aplikasi Teknologi Informasi 2005, SNATI 2005 ; Conference date: 18-06-2005 Through 18-06-2005",

}

TY - CONF

T1 - Histograms in Breast Density Classification

T2 - Seminar Nasional Aplikasi Teknologi Informasi 2005

AU - Muhimmah, Izzati

AU - Denton, Erika R. E.

AU - Zwiggelaar, Reyer

PY - 2005/6/18

Y1 - 2005/6/18

N2 - Breast density is known to be an important indicator of breast cancer risk. Quantitative estimation approaches have been developed and some of these are based on grey level or texture metrics. Developing an example of the former, we combined multi-resolution histograms and pattern matching approaches. The results show good agreement compared to expert radiologist classification. The presented approach provides similar results to existing methods and limitations are discussed.

AB - Breast density is known to be an important indicator of breast cancer risk. Quantitative estimation approaches have been developed and some of these are based on grey level or texture metrics. Developing an example of the former, we combined multi-resolution histograms and pattern matching approaches. The results show good agreement compared to expert radiologist classification. The presented approach provides similar results to existing methods and limitations are discussed.

KW - Multi-Resolution Histogram Technique

KW - Mammography

KW - Breast Density Classification

M3 - Paper

Y2 - 18 June 2005 through 18 June 2005

ER -

Histograms in Breast Density Classification: Are 4 better than 1?

Abstract

Seminar

Keywords

UN SDGs

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