Breast tissue classification in mammograms using visual words

Idit Diamant; Hayit Greenspan; Jacob Goldberger

doi:10.1109/eeei.2012.6377061

Breast tissue classification in mammograms using visual words

Idit Diamant
, Hayit Greenspan
, Jacob Goldberger

Bar-Ilan University - The Alexander Kofkin Faculty of Engineering

Tel Aviv University

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

2 Scopus citations

Abstract

The presence of Microcalcifications is an important indicator for developing breast cancer. Additional indicators for cancer risk exist, such as breast tissue density type. Different methods have been developed for breast tissue classification for use in CAD systems. Recently, the visual words (VW) model has been successfully applied for different classification tasks. The goal of our work is to explore VW based methodologies for various mammography classification tasks. We start with the challenge of classifying breast density and then focus on classification of normal tissue versus Microcalcifications. Classification tasks were performed using Support Vector Machine. The results demonstrate the feasibility to classify breast tissue using our model. Currently, we are investigating VW capability to classify additional mammogram classification problems, suggesting new means for automated tools for mammography diagnosis support.

Original language	English
Title of host publication	2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012
DOIs	https://doi.org/10.1109/eeei.2012.6377061
State	Published - 2012
Event	2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012 - Eilat, Israel Duration: 14 Nov 2012 → 17 Nov 2012

Publication series

Name	2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012

Conference

Conference	2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012
Country/Territory	Israel
City	Eilat
Period	14/11/12 → 17/11/12

UN SDGs

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

SDG 3 Good Health and Well-being

Keywords

Visual words
calcifications
classification
mammography

Access to Document

10.1109/eeei.2012.6377061

Cite this

@inproceedings{2a81835f3c69408fa4ae6cddb36fd1c9,

title = "Breast tissue classification in mammograms using visual words",

abstract = "The presence of Microcalcifications is an important indicator for developing breast cancer. Additional indicators for cancer risk exist, such as breast tissue density type. Different methods have been developed for breast tissue classification for use in CAD systems. Recently, the visual words (VW) model has been successfully applied for different classification tasks. The goal of our work is to explore VW based methodologies for various mammography classification tasks. We start with the challenge of classifying breast density and then focus on classification of normal tissue versus Microcalcifications. Classification tasks were performed using Support Vector Machine. The results demonstrate the feasibility to classify breast tissue using our model. Currently, we are investigating VW capability to classify additional mammogram classification problems, suggesting new means for automated tools for mammography diagnosis support.",

keywords = "Visual words, calcifications, classification, mammography",

author = "Idit Diamant and Hayit Greenspan and Jacob Goldberger",

year = "2012",

doi = "10.1109/eeei.2012.6377061",

language = "אנגלית",

isbn = "9781467346801",

series = "2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012",

booktitle = "2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012",

note = "2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012 ; Conference date: 14-11-2012 Through 17-11-2012",

}

Diamant, I, Greenspan, H & Goldberger, J 2012, Breast tissue classification in mammograms using visual words. in 2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012., 6377061, 2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012, 2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012, Eilat, Israel, 14/11/12. https://doi.org/10.1109/eeei.2012.6377061

Breast tissue classification in mammograms using visual words. / Diamant, Idit; Greenspan, Hayit; Goldberger, Jacob.
2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012. 2012. 6377061 (2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012).

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

TY - GEN

T1 - Breast tissue classification in mammograms using visual words

AU - Diamant, Idit

AU - Greenspan, Hayit

AU - Goldberger, Jacob

PY - 2012

Y1 - 2012

N2 - The presence of Microcalcifications is an important indicator for developing breast cancer. Additional indicators for cancer risk exist, such as breast tissue density type. Different methods have been developed for breast tissue classification for use in CAD systems. Recently, the visual words (VW) model has been successfully applied for different classification tasks. The goal of our work is to explore VW based methodologies for various mammography classification tasks. We start with the challenge of classifying breast density and then focus on classification of normal tissue versus Microcalcifications. Classification tasks were performed using Support Vector Machine. The results demonstrate the feasibility to classify breast tissue using our model. Currently, we are investigating VW capability to classify additional mammogram classification problems, suggesting new means for automated tools for mammography diagnosis support.

AB - The presence of Microcalcifications is an important indicator for developing breast cancer. Additional indicators for cancer risk exist, such as breast tissue density type. Different methods have been developed for breast tissue classification for use in CAD systems. Recently, the visual words (VW) model has been successfully applied for different classification tasks. The goal of our work is to explore VW based methodologies for various mammography classification tasks. We start with the challenge of classifying breast density and then focus on classification of normal tissue versus Microcalcifications. Classification tasks were performed using Support Vector Machine. The results demonstrate the feasibility to classify breast tissue using our model. Currently, we are investigating VW capability to classify additional mammogram classification problems, suggesting new means for automated tools for mammography diagnosis support.

KW - Visual words

KW - calcifications

KW - classification

KW - mammography

UR - https://www.scopus.com/pages/publications/84871958703

U2 - 10.1109/eeei.2012.6377061

DO - 10.1109/eeei.2012.6377061

M3 - ???researchoutput.researchoutputtypes.contributiontobookanthology.conference???

AN - SCOPUS:84871958703

SN - 9781467346801

T3 - 2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012

BT - 2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012

T2 - 2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012

Y2 - 14 November 2012 through 17 November 2012

ER -

Breast tissue classification in mammograms using visual words

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Cite this