Breast Lesion Segmentation in DCE- MRI Imaging

Zuzanna Koper; Mariusz Frackiewicz; Henryk Palus; Damian Borys; Krzysztof Psiuk-Maksymowicz

doi:10.1109/SITIS.2018.00054

Breast Lesion Segmentation in DCE- MRI Imaging

Silesian University of Technology

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

11 Citations (Scopus)

Abstract

Breast cancer is one of the most common cancers in women. Typically, the course of the disease is asymptomatic in the early stages of breast cancer. Imaging breast examinations allow early detection of the cancer, which is associated with increased chances of a complete cure. There are many breast imaging techniques such as: mammography (MM), ultrasound imaging (US), positron-emission tomography (PET), computed tomography (CT), and magnetic resonance imaging (MRI). These imaging techniques differ in terms of effectiveness, price, type of physical phenomenon, the impact on the patient and its availability. In this paper, we focus on MRI imaging and we compare three breast lesion segmentation algorithms that have been tested on QIN Breast DCE-MRI database, which is publicly available. The obtained values of Dice and Jaccard indices indicate the segmentation using k-means algorithm.

Original language	English
Title of host publication	Proceedings - 14th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2018
Editors	Richard Chbeir, Gabriella Sanniti di Baja, Luigi Gallo, Kokou Yetongnon, Albert Dipanda, Modesto Castrillon-Santana
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	308-313
Number of pages	6
ISBN (Electronic)	9781538693858
DOIs	https://doi.org/10.1109/SITIS.2018.00054
Publication status	Published - 2 Jul 2018
Event	14th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2018 - Las Palmas de Gran Canaria, Spain Duration: 26 Nov 2018 → 29 Nov 2018

Publication series

Name	Proceedings - 14th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2018

Conference

Conference	14th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2018
Country/Territory	Spain
City	Las Palmas de Gran Canaria
Period	26/11/18 → 29/11/18

UN SDGs

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

SDG 3 Good Health and Well-being

Keywords

Breast lesion segmentation
DCE-MRI
Medical imaging

ASJC Scopus subject areas

Computer Networks and Communications
Computer Vision and Pattern Recognition

Access to Document

10.1109/SITIS.2018.00054

Cite this

Koper, Z., Frackiewicz, M., Palus, H., Borys, D., & Psiuk-Maksymowicz, K. (2018). Breast Lesion Segmentation in DCE- MRI Imaging. In R. Chbeir, G. S. di Baja, L. Gallo, K. Yetongnon, A. Dipanda, & M. Castrillon-Santana (Eds.), Proceedings - 14th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2018 (pp. 308-313). Article 8706227 (Proceedings - 14th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SITIS.2018.00054

Koper, Zuzanna ; Frackiewicz, Mariusz ; Palus, Henryk et al. / Breast Lesion Segmentation in DCE- MRI Imaging. Proceedings - 14th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2018. editor / Richard Chbeir ; Gabriella Sanniti di Baja ; Luigi Gallo ; Kokou Yetongnon ; Albert Dipanda ; Modesto Castrillon-Santana. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 308-313 (Proceedings - 14th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2018).

@inproceedings{df638b5064c8450c99a0d54b4fc77633,

title = "Breast Lesion Segmentation in DCE- MRI Imaging",

abstract = "Breast cancer is one of the most common cancers in women. Typically, the course of the disease is asymptomatic in the early stages of breast cancer. Imaging breast examinations allow early detection of the cancer, which is associated with increased chances of a complete cure. There are many breast imaging techniques such as: mammography (MM), ultrasound imaging (US), positron-emission tomography (PET), computed tomography (CT), and magnetic resonance imaging (MRI). These imaging techniques differ in terms of effectiveness, price, type of physical phenomenon, the impact on the patient and its availability. In this paper, we focus on MRI imaging and we compare three breast lesion segmentation algorithms that have been tested on QIN Breast DCE-MRI database, which is publicly available. The obtained values of Dice and Jaccard indices indicate the segmentation using k-means algorithm.",

keywords = "Breast lesion segmentation, DCE-MRI, Medical imaging",

author = "Zuzanna Koper and Mariusz Frackiewicz and Henryk Palus and Damian Borys and Krzysztof Psiuk-Maksymowicz",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 14th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2018 ; Conference date: 26-11-2018 Through 29-11-2018",

year = "2018",

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doi = "10.1109/SITIS.2018.00054",

language = "English",

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Koper, Z, Frackiewicz, M , Palus, H , Borys, D & Psiuk-Maksymowicz, K 2018, Breast Lesion Segmentation in DCE- MRI Imaging. in R Chbeir, GS di Baja, L Gallo, K Yetongnon, A Dipanda & M Castrillon-Santana (eds), Proceedings - 14th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2018., 8706227, Proceedings - 14th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2018, Institute of Electrical and Electronics Engineers Inc., pp. 308-313, 14th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2018, Las Palmas de Gran Canaria, Spain, 26/11/18. https://doi.org/10.1109/SITIS.2018.00054

Breast Lesion Segmentation in DCE- MRI Imaging. / Koper, Zuzanna; Frackiewicz, Mariusz ; Palus, Henryk et al.
Proceedings - 14th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2018. ed. / Richard Chbeir; Gabriella Sanniti di Baja; Luigi Gallo; Kokou Yetongnon; Albert Dipanda; Modesto Castrillon-Santana. Institute of Electrical and Electronics Engineers Inc., 2018. p. 308-313 8706227 (Proceedings - 14th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2018).

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

TY - GEN

T1 - Breast Lesion Segmentation in DCE- MRI Imaging

AU - Koper, Zuzanna

AU - Frackiewicz, Mariusz

AU - Palus, Henryk

AU - Borys, Damian

AU - Psiuk-Maksymowicz, Krzysztof

PY - 2018/7/2

Y1 - 2018/7/2

N2 - Breast cancer is one of the most common cancers in women. Typically, the course of the disease is asymptomatic in the early stages of breast cancer. Imaging breast examinations allow early detection of the cancer, which is associated with increased chances of a complete cure. There are many breast imaging techniques such as: mammography (MM), ultrasound imaging (US), positron-emission tomography (PET), computed tomography (CT), and magnetic resonance imaging (MRI). These imaging techniques differ in terms of effectiveness, price, type of physical phenomenon, the impact on the patient and its availability. In this paper, we focus on MRI imaging and we compare three breast lesion segmentation algorithms that have been tested on QIN Breast DCE-MRI database, which is publicly available. The obtained values of Dice and Jaccard indices indicate the segmentation using k-means algorithm.

AB - Breast cancer is one of the most common cancers in women. Typically, the course of the disease is asymptomatic in the early stages of breast cancer. Imaging breast examinations allow early detection of the cancer, which is associated with increased chances of a complete cure. There are many breast imaging techniques such as: mammography (MM), ultrasound imaging (US), positron-emission tomography (PET), computed tomography (CT), and magnetic resonance imaging (MRI). These imaging techniques differ in terms of effectiveness, price, type of physical phenomenon, the impact on the patient and its availability. In this paper, we focus on MRI imaging and we compare three breast lesion segmentation algorithms that have been tested on QIN Breast DCE-MRI database, which is publicly available. The obtained values of Dice and Jaccard indices indicate the segmentation using k-means algorithm.

KW - Breast lesion segmentation

KW - DCE-MRI

KW - Medical imaging

UR - https://www.scopus.com/pages/publications/85065906642

U2 - 10.1109/SITIS.2018.00054

DO - 10.1109/SITIS.2018.00054

M3 - Conference contribution

AN - SCOPUS:85065906642

T3 - Proceedings - 14th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2018

SP - 308

EP - 313

BT - Proceedings - 14th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2018

A2 - Chbeir, Richard

A2 - di Baja, Gabriella Sanniti

A2 - Gallo, Luigi

A2 - Yetongnon, Kokou

A2 - Dipanda, Albert

A2 - Castrillon-Santana, Modesto

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 14th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2018

Y2 - 26 November 2018 through 29 November 2018

ER -

Koper Z, Frackiewicz M , Palus H , Borys D , Psiuk-Maksymowicz K. Breast Lesion Segmentation in DCE- MRI Imaging. In Chbeir R, di Baja GS, Gallo L, Yetongnon K, Dipanda A, Castrillon-Santana M, editors, Proceedings - 14th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 308-313. 8706227. (Proceedings - 14th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2018). doi: 10.1109/SITIS.2018.00054

Breast Lesion Segmentation in DCE- MRI Imaging

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

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