Development of a peripheral thickness estimation method for volumetric breast density measurements in mammography using a 3D finite element breast model

Olivier Alonzo-Proulx, James G. Mainprize, Nathan J. Packard, John M Boone, Adil Al-Mayah, Kristy Brock, Martin J. Yaffe

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

A method was developed to determine the area in a mammogram where the breast is not in contact with the compression paddle (the periphery), and to predict the breast thickness in that peripheral region. The periphery is determined by evaluating the variation of the signal intensity along radial lines, and the peripheral thickness is modeled assuming the breast has a semi-circular shape. The method was tested on 26 simulated mammograms for which the volumetric information was available. The mammograms were obtained using CT data that were deformed to simulate mammographic compression and then projected using a physical model. The method predicted the thickness in the periphery to within 3.3 mm of the actual value and the volumetric breast density within 4.3 percentage points. The method was also tested on 209 digital mammograms, and on average it was estimated that thickness errors occurred on 9% of the breast image, and the average absolute thickness error on those points was estimated to be approximately 2.0 mm in the periphery and central region of the breast but as large as 10.5 mm in the extreme periphery where the thickness is small.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages467-473
Number of pages7
Volume6136 LNCS
DOIs
StatePublished - 2010
Event10th International Workshop on Digital Mammography, IWDM 2010 - Girona, Catalonia, Spain
Duration: Jun 16 2010Jun 18 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6136 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other10th International Workshop on Digital Mammography, IWDM 2010
CountrySpain
CityGirona, Catalonia
Period6/16/106/18/10

Fingerprint

Mammography
Mammogram
Finite Element
Compression
Model
Percentage Points
Physical Model
Extremes
Contact
Predict
Line
Mm

Keywords

  • digital mammography
  • periphery detection
  • volumetric breast density

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Alonzo-Proulx, O., Mainprize, J. G., Packard, N. J., Boone, J. M., Al-Mayah, A., Brock, K., & Yaffe, M. J. (2010). Development of a peripheral thickness estimation method for volumetric breast density measurements in mammography using a 3D finite element breast model. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6136 LNCS, pp. 467-473). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6136 LNCS). https://doi.org/10.1007/978-3-642-13666-5_63

Development of a peripheral thickness estimation method for volumetric breast density measurements in mammography using a 3D finite element breast model. / Alonzo-Proulx, Olivier; Mainprize, James G.; Packard, Nathan J.; Boone, John M; Al-Mayah, Adil; Brock, Kristy; Yaffe, Martin J.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6136 LNCS 2010. p. 467-473 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6136 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Alonzo-Proulx, O, Mainprize, JG, Packard, NJ, Boone, JM, Al-Mayah, A, Brock, K & Yaffe, MJ 2010, Development of a peripheral thickness estimation method for volumetric breast density measurements in mammography using a 3D finite element breast model. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 6136 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6136 LNCS, pp. 467-473, 10th International Workshop on Digital Mammography, IWDM 2010, Girona, Catalonia, Spain, 6/16/10. https://doi.org/10.1007/978-3-642-13666-5_63
Alonzo-Proulx O, Mainprize JG, Packard NJ, Boone JM, Al-Mayah A, Brock K et al. Development of a peripheral thickness estimation method for volumetric breast density measurements in mammography using a 3D finite element breast model. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6136 LNCS. 2010. p. 467-473. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-13666-5_63
Alonzo-Proulx, Olivier ; Mainprize, James G. ; Packard, Nathan J. ; Boone, John M ; Al-Mayah, Adil ; Brock, Kristy ; Yaffe, Martin J. / Development of a peripheral thickness estimation method for volumetric breast density measurements in mammography using a 3D finite element breast model. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6136 LNCS 2010. pp. 467-473 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{e8be94ecadda4e9e8aee1c36ec5ac22f,
title = "Development of a peripheral thickness estimation method for volumetric breast density measurements in mammography using a 3D finite element breast model",
abstract = "A method was developed to determine the area in a mammogram where the breast is not in contact with the compression paddle (the periphery), and to predict the breast thickness in that peripheral region. The periphery is determined by evaluating the variation of the signal intensity along radial lines, and the peripheral thickness is modeled assuming the breast has a semi-circular shape. The method was tested on 26 simulated mammograms for which the volumetric information was available. The mammograms were obtained using CT data that were deformed to simulate mammographic compression and then projected using a physical model. The method predicted the thickness in the periphery to within 3.3 mm of the actual value and the volumetric breast density within 4.3 percentage points. The method was also tested on 209 digital mammograms, and on average it was estimated that thickness errors occurred on 9{\%} of the breast image, and the average absolute thickness error on those points was estimated to be approximately 2.0 mm in the periphery and central region of the breast but as large as 10.5 mm in the extreme periphery where the thickness is small.",
keywords = "digital mammography, periphery detection, volumetric breast density",
author = "Olivier Alonzo-Proulx and Mainprize, {James G.} and Packard, {Nathan J.} and Boone, {John M} and Adil Al-Mayah and Kristy Brock and Yaffe, {Martin J.}",
year = "2010",
doi = "10.1007/978-3-642-13666-5_63",
language = "English (US)",
isbn = "3642136656",
volume = "6136 LNCS",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "467--473",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

}

TY - GEN

T1 - Development of a peripheral thickness estimation method for volumetric breast density measurements in mammography using a 3D finite element breast model

AU - Alonzo-Proulx, Olivier

AU - Mainprize, James G.

AU - Packard, Nathan J.

AU - Boone, John M

AU - Al-Mayah, Adil

AU - Brock, Kristy

AU - Yaffe, Martin J.

PY - 2010

Y1 - 2010

N2 - A method was developed to determine the area in a mammogram where the breast is not in contact with the compression paddle (the periphery), and to predict the breast thickness in that peripheral region. The periphery is determined by evaluating the variation of the signal intensity along radial lines, and the peripheral thickness is modeled assuming the breast has a semi-circular shape. The method was tested on 26 simulated mammograms for which the volumetric information was available. The mammograms were obtained using CT data that were deformed to simulate mammographic compression and then projected using a physical model. The method predicted the thickness in the periphery to within 3.3 mm of the actual value and the volumetric breast density within 4.3 percentage points. The method was also tested on 209 digital mammograms, and on average it was estimated that thickness errors occurred on 9% of the breast image, and the average absolute thickness error on those points was estimated to be approximately 2.0 mm in the periphery and central region of the breast but as large as 10.5 mm in the extreme periphery where the thickness is small.

AB - A method was developed to determine the area in a mammogram where the breast is not in contact with the compression paddle (the periphery), and to predict the breast thickness in that peripheral region. The periphery is determined by evaluating the variation of the signal intensity along radial lines, and the peripheral thickness is modeled assuming the breast has a semi-circular shape. The method was tested on 26 simulated mammograms for which the volumetric information was available. The mammograms were obtained using CT data that were deformed to simulate mammographic compression and then projected using a physical model. The method predicted the thickness in the periphery to within 3.3 mm of the actual value and the volumetric breast density within 4.3 percentage points. The method was also tested on 209 digital mammograms, and on average it was estimated that thickness errors occurred on 9% of the breast image, and the average absolute thickness error on those points was estimated to be approximately 2.0 mm in the periphery and central region of the breast but as large as 10.5 mm in the extreme periphery where the thickness is small.

KW - digital mammography

KW - periphery detection

KW - volumetric breast density

UR - http://www.scopus.com/inward/record.url?scp=77954651008&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77954651008&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-13666-5_63

DO - 10.1007/978-3-642-13666-5_63

M3 - Conference contribution

AN - SCOPUS:77954651008

SN - 3642136656

SN - 9783642136658

VL - 6136 LNCS

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 467

EP - 473

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

ER -