Modelling structural deformations in mammographic tissue using the dual-tree complex wavelet

Michael Berks; Chris Taylor; Rumana Rahim; Caroline Boggis; Susan Astley

doi:10.1007/978-3-642-13666-5_20

Modelling structural deformations in mammographic tissue using the dual-tree complex wavelet

Michael Berks, Chris Taylor, Rumana Rahim, Caroline Boggis, Susan Astley

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

Abstract

The appearance of breast tissue in mammograms is altered by the presence of a malignant mass. Existing synthesis methods have not addressed this structural deformation. We aim to use a set of mass background images that display altered breast tissue to simulate such deformations in regions of digital mammograms previously showing no signs of disease. Regions are decomposed using the dual-tree complex wavelet transform (DT-CWT) to obtain a richer representation of local structure than provided by image grey-levels alone. Synthesis is achieved by modifying the high-frequency DT-CWT coefficients of normal regions to match those in mass backgrounds. Three methods for completing this task are described. The results, advantages and current limitations of the methods are discussed. © 2010 Springer-Verlag.

Original language	English
Pages (from-to)	145-152
Number of pages	7
Journal	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	6136
DOIs	https://doi.org/10.1007/978-3-642-13666-5_20
Publication status	Published - 2010

Keywords

dual-tree complex wavelet transform
lesion synthesis
malignant mass
Mammography
texture models
tissue deformation

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10.1007/978-3-642-13666-5_20

Cite this

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title = "Modelling structural deformations in mammographic tissue using the dual-tree complex wavelet",

abstract = "The appearance of breast tissue in mammograms is altered by the presence of a malignant mass. Existing synthesis methods have not addressed this structural deformation. We aim to use a set of mass background images that display altered breast tissue to simulate such deformations in regions of digital mammograms previously showing no signs of disease. Regions are decomposed using the dual-tree complex wavelet transform (DT-CWT) to obtain a richer representation of local structure than provided by image grey-levels alone. Synthesis is achieved by modifying the high-frequency DT-CWT coefficients of normal regions to match those in mass backgrounds. Three methods for completing this task are described. The results, advantages and current limitations of the methods are discussed. {\textcopyright} 2010 Springer-Verlag.",

keywords = "dual-tree complex wavelet transform, lesion synthesis, malignant mass, Mammography, texture models, tissue deformation",

author = "Michael Berks and Chris Taylor and Rumana Rahim and Caroline Boggis and Susan Astley",

year = "2010",

doi = "10.1007/978-3-642-13666-5_20",

language = "English",

volume = "6136",

pages = "145--152",

journal = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

issn = "0302-9743",

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Modelling structural deformations in mammographic tissue using the dual-tree complex wavelet. / Berks, Michael ; Taylor, Chris; Rahim, Rumana et al.
In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 6136, 2010, p. 145-152.

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

TY - JOUR

T1 - Modelling structural deformations in mammographic tissue using the dual-tree complex wavelet

AU - Berks, Michael

AU - Taylor, Chris

AU - Rahim, Rumana

AU - Boggis, Caroline

AU - Astley, Susan

PY - 2010

Y1 - 2010

N2 - The appearance of breast tissue in mammograms is altered by the presence of a malignant mass. Existing synthesis methods have not addressed this structural deformation. We aim to use a set of mass background images that display altered breast tissue to simulate such deformations in regions of digital mammograms previously showing no signs of disease. Regions are decomposed using the dual-tree complex wavelet transform (DT-CWT) to obtain a richer representation of local structure than provided by image grey-levels alone. Synthesis is achieved by modifying the high-frequency DT-CWT coefficients of normal regions to match those in mass backgrounds. Three methods for completing this task are described. The results, advantages and current limitations of the methods are discussed. © 2010 Springer-Verlag.

AB - The appearance of breast tissue in mammograms is altered by the presence of a malignant mass. Existing synthesis methods have not addressed this structural deformation. We aim to use a set of mass background images that display altered breast tissue to simulate such deformations in regions of digital mammograms previously showing no signs of disease. Regions are decomposed using the dual-tree complex wavelet transform (DT-CWT) to obtain a richer representation of local structure than provided by image grey-levels alone. Synthesis is achieved by modifying the high-frequency DT-CWT coefficients of normal regions to match those in mass backgrounds. Three methods for completing this task are described. The results, advantages and current limitations of the methods are discussed. © 2010 Springer-Verlag.

KW - dual-tree complex wavelet transform

KW - lesion synthesis

KW - malignant mass

KW - Mammography

KW - texture models

KW - tissue deformation

U2 - 10.1007/978-3-642-13666-5_20

DO - 10.1007/978-3-642-13666-5_20

M3 - Article

SN - 0302-9743

VL - 6136

SP - 145

EP - 152

JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ER -

Modelling structural deformations in mammographic tissue using the dual-tree complex wavelet

Abstract

Keywords

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