Model based approach to object detection in digital mammography

Steven Morrison; Laurie M. Linnett

doi:10.1109/ICIP.1999.822880

Model based approach to object detection in digital mammography

Steven Morrison, Laurie M. Linnett

School of Mathematical & Computer Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

11 Citations (Scopus)

Abstract

Breast cancer has the highest incidence level of any cancer among women living in developed countries. Early detection of masses, and microcalcification clusters, is presently the best means whereby breast cancer mortality rates may be reduced. To this end, high resolution digital mammograms, generally at the 50 µm resolution, are used with a view to automatically detecting any potential anomalies. This paper presents an original technique for the detection of such microcalcifications. This is done by specifying a parametric model, and using this to gain estimates of object positions and sizes directly.

Original language	English
Title of host publication	Proceedings of the International Conference on Image Processing, 1999
Pages	182-186
Number of pages	5
Volume	2
DOIs	https://doi.org/10.1109/ICIP.1999.822880
Publication status	Published - 1999
Event	6th IEEE International Conference on Image Processing 1999 - Kobe, Japan Duration: 24 Oct 1999 → 28 Oct 1999

Conference

Conference	6th IEEE International Conference on Image Processing 1999
Abbreviated title	ICIP 1999
Country/Territory	Japan
City	Kobe
Period	24/10/99 → 28/10/99

UN SDGs

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

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10.1109/ICIP.1999.822880

Cite this

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title = "Model based approach to object detection in digital mammography",

abstract = "Breast cancer has the highest incidence level of any cancer among women living in developed countries. Early detection of masses, and microcalcification clusters, is presently the best means whereby breast cancer mortality rates may be reduced. To this end, high resolution digital mammograms, generally at the 50 µm resolution, are used with a view to automatically detecting any potential anomalies. This paper presents an original technique for the detection of such microcalcifications. This is done by specifying a parametric model, and using this to gain estimates of object positions and sizes directly.",

author = "Steven Morrison and Linnett, {Laurie M.}",

note = "INSPEC Accession Number: 6514181; 6th IEEE International Conference on Image Processing 1999, ICIP 1999 ; Conference date: 24-10-1999 Through 28-10-1999",

year = "1999",

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language = "English",

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AU - Linnett, Laurie M.

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N2 - Breast cancer has the highest incidence level of any cancer among women living in developed countries. Early detection of masses, and microcalcification clusters, is presently the best means whereby breast cancer mortality rates may be reduced. To this end, high resolution digital mammograms, generally at the 50 µm resolution, are used with a view to automatically detecting any potential anomalies. This paper presents an original technique for the detection of such microcalcifications. This is done by specifying a parametric model, and using this to gain estimates of object positions and sizes directly.

AB - Breast cancer has the highest incidence level of any cancer among women living in developed countries. Early detection of masses, and microcalcification clusters, is presently the best means whereby breast cancer mortality rates may be reduced. To this end, high resolution digital mammograms, generally at the 50 µm resolution, are used with a view to automatically detecting any potential anomalies. This paper presents an original technique for the detection of such microcalcifications. This is done by specifying a parametric model, and using this to gain estimates of object positions and sizes directly.

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U2 - 10.1109/ICIP.1999.822880

DO - 10.1109/ICIP.1999.822880

M3 - Conference contribution

SN - 0-7803-5467-2

VL - 2

SP - 182

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BT - Proceedings of the International Conference on Image Processing, 1999

T2 - 6th IEEE International Conference on Image Processing 1999

Y2 - 24 October 1999 through 28 October 1999

ER -

Model based approach to object detection in digital mammography

Abstract

Conference

UN SDGs

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