Joint myocardial registration and segmentation of cardiac BOLD MRI

Ilkay Oksuz; Rohan Dharmakumar; Sotirios A. Tsaftaris

doi:10.1007/978-3-319-75541-0_2

Joint myocardial registration and segmentation of cardiac BOLD MRI

Ilkay Oksuz^*, Rohan Dharmakumar, Sotirios A. Tsaftaris

^*Corresponding author for this work

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

1 Citation (Scopus)

Abstract

Registration and segmentation of anatomical structures are two well studied problems in medical imaging. Optimizing segmentation and registration jointly has been proven to improve results for both challenges. In this work, we propose a joint optimization scheme for registration and segmentation using dictionary learning based descriptors. Our joint registration and segmentation aims to solve an optimization function, which enables better performance for both of these ill-posed processes. We build two dictionaries for background and myocardium for square patches extracted from training images. Based on dictionary learning residuals and sparse representations defined on these pre-trained dictionaries, a Markov Random Field (MRF) based joint optimization scheme is built. The algorithm proceeds iteratively updating the dictionaries in an online fashion. The accuracy of the proposed method is illustrated on Cardiac Phase-resolved Blood Oxygen-Level-Dependent (CP-BOLD) MRI and standard cine Cardiac MRI data from MICCAI 2013 SATA Segmentation Challenge. The proposed joint segmentation and registration method achieves higher dice accuracy for myocardium segmentation compared to its variants.

Original language	English
Title of host publication	Statistical Atlases and Computational Models of the Heart
Subtitle of host publication	ACDC and MMWHS Challenges - 8th International Workshop, STACOM 2017, Revised Selected Papers
Editors	Olivier Bernard, Pierre-Marc Jodoin, Xiahai Zhuang, Guang Yang, Alistair Young, Maxime Sermesant, Alain Lalande, Mihaela Pop
Publisher	Springer Verlag
Pages	12-20
Number of pages	9
ISBN (Print)	9783319755403
DOIs	https://doi.org/10.1007/978-3-319-75541-0_2
Publication status	Published - 2018
Externally published	Yes
Event	8th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2017, Held in Conjunction with MICCAI 2017 - Quebec City, Canada Duration: 10 Sept 2017 → 14 Sept 2017

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10663 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	8th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2017, Held in Conjunction with MICCAI 2017
Country/Territory	Canada
City	Quebec City
Period	10/09/17 → 14/09/17

Bibliographical note

Publisher Copyright:
© Springer International Publishing AG, part of Springer Nature 2018.

Keywords

BOLD
CINE MR
Joint optimization
Markov random fields
Registration
Segmentation

Access to Document

10.1007/978-3-319-75541-0_2

Cite this

Oksuz, I., Dharmakumar, R., & Tsaftaris, S. A. (2018). Joint myocardial registration and segmentation of cardiac BOLD MRI. In O. Bernard, P.-M. Jodoin, X. Zhuang, G. Yang, A. Young, M. Sermesant, A. Lalande, & M. Pop (Eds.), Statistical Atlases and Computational Models of the Heart: ACDC and MMWHS Challenges - 8th International Workshop, STACOM 2017, Revised Selected Papers (pp. 12-20). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10663 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-75541-0_2

Oksuz, Ilkay ; Dharmakumar, Rohan ; Tsaftaris, Sotirios A. / Joint myocardial registration and segmentation of cardiac BOLD MRI. Statistical Atlases and Computational Models of the Heart: ACDC and MMWHS Challenges - 8th International Workshop, STACOM 2017, Revised Selected Papers. editor / Olivier Bernard ; Pierre-Marc Jodoin ; Xiahai Zhuang ; Guang Yang ; Alistair Young ; Maxime Sermesant ; Alain Lalande ; Mihaela Pop. Springer Verlag, 2018. pp. 12-20 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{1175a412d2ef48dca4ffb685dbddc821,

title = "Joint myocardial registration and segmentation of cardiac BOLD MRI",

abstract = "Registration and segmentation of anatomical structures are two well studied problems in medical imaging. Optimizing segmentation and registration jointly has been proven to improve results for both challenges. In this work, we propose a joint optimization scheme for registration and segmentation using dictionary learning based descriptors. Our joint registration and segmentation aims to solve an optimization function, which enables better performance for both of these ill-posed processes. We build two dictionaries for background and myocardium for square patches extracted from training images. Based on dictionary learning residuals and sparse representations defined on these pre-trained dictionaries, a Markov Random Field (MRF) based joint optimization scheme is built. The algorithm proceeds iteratively updating the dictionaries in an online fashion. The accuracy of the proposed method is illustrated on Cardiac Phase-resolved Blood Oxygen-Level-Dependent (CP-BOLD) MRI and standard cine Cardiac MRI data from MICCAI 2013 SATA Segmentation Challenge. The proposed joint segmentation and registration method achieves higher dice accuracy for myocardium segmentation compared to its variants.",

keywords = "BOLD, CINE MR, Joint optimization, Markov random fields, Registration, Segmentation",

author = "Ilkay Oksuz and Rohan Dharmakumar and Tsaftaris, {Sotirios A.}",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG, part of Springer Nature 2018.; 8th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2017, Held in Conjunction with MICCAI 2017 ; Conference date: 10-09-2017 Through 14-09-2017",

year = "2018",

doi = "10.1007/978-3-319-75541-0_2",

language = "English",

isbn = "9783319755403",

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

publisher = "Springer Verlag",

pages = "12--20",

editor = "Olivier Bernard and Pierre-Marc Jodoin and Xiahai Zhuang and Guang Yang and Alistair Young and Maxime Sermesant and Alain Lalande and Mihaela Pop",

booktitle = "Statistical Atlases and Computational Models of the Heart",

address = "Germany",

}

Oksuz, I, Dharmakumar, R & Tsaftaris, SA 2018, Joint myocardial registration and segmentation of cardiac BOLD MRI. in O Bernard, P-M Jodoin, X Zhuang, G Yang, A Young, M Sermesant, A Lalande & M Pop (eds), Statistical Atlases and Computational Models of the Heart: ACDC and MMWHS Challenges - 8th International Workshop, STACOM 2017, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10663 LNCS, Springer Verlag, pp. 12-20, 8th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2017, Held in Conjunction with MICCAI 2017, Quebec City, Canada, 10/09/17. https://doi.org/10.1007/978-3-319-75541-0_2

Joint myocardial registration and segmentation of cardiac BOLD MRI. / Oksuz, Ilkay; Dharmakumar, Rohan; Tsaftaris, Sotirios A.
Statistical Atlases and Computational Models of the Heart: ACDC and MMWHS Challenges - 8th International Workshop, STACOM 2017, Revised Selected Papers. ed. / Olivier Bernard; Pierre-Marc Jodoin; Xiahai Zhuang; Guang Yang; Alistair Young; Maxime Sermesant; Alain Lalande; Mihaela Pop. Springer Verlag, 2018. p. 12-20 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10663 LNCS).

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

TY - GEN

T1 - Joint myocardial registration and segmentation of cardiac BOLD MRI

AU - Oksuz, Ilkay

AU - Dharmakumar, Rohan

AU - Tsaftaris, Sotirios A.

N1 - Publisher Copyright: © Springer International Publishing AG, part of Springer Nature 2018.

PY - 2018

Y1 - 2018

N2 - Registration and segmentation of anatomical structures are two well studied problems in medical imaging. Optimizing segmentation and registration jointly has been proven to improve results for both challenges. In this work, we propose a joint optimization scheme for registration and segmentation using dictionary learning based descriptors. Our joint registration and segmentation aims to solve an optimization function, which enables better performance for both of these ill-posed processes. We build two dictionaries for background and myocardium for square patches extracted from training images. Based on dictionary learning residuals and sparse representations defined on these pre-trained dictionaries, a Markov Random Field (MRF) based joint optimization scheme is built. The algorithm proceeds iteratively updating the dictionaries in an online fashion. The accuracy of the proposed method is illustrated on Cardiac Phase-resolved Blood Oxygen-Level-Dependent (CP-BOLD) MRI and standard cine Cardiac MRI data from MICCAI 2013 SATA Segmentation Challenge. The proposed joint segmentation and registration method achieves higher dice accuracy for myocardium segmentation compared to its variants.

AB - Registration and segmentation of anatomical structures are two well studied problems in medical imaging. Optimizing segmentation and registration jointly has been proven to improve results for both challenges. In this work, we propose a joint optimization scheme for registration and segmentation using dictionary learning based descriptors. Our joint registration and segmentation aims to solve an optimization function, which enables better performance for both of these ill-posed processes. We build two dictionaries for background and myocardium for square patches extracted from training images. Based on dictionary learning residuals and sparse representations defined on these pre-trained dictionaries, a Markov Random Field (MRF) based joint optimization scheme is built. The algorithm proceeds iteratively updating the dictionaries in an online fashion. The accuracy of the proposed method is illustrated on Cardiac Phase-resolved Blood Oxygen-Level-Dependent (CP-BOLD) MRI and standard cine Cardiac MRI data from MICCAI 2013 SATA Segmentation Challenge. The proposed joint segmentation and registration method achieves higher dice accuracy for myocardium segmentation compared to its variants.

KW - BOLD

KW - CINE MR

KW - Joint optimization

KW - Markov random fields

KW - Registration

KW - Segmentation

UR - http://www.scopus.com/inward/record.url?scp=85044468353&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-75541-0_2

DO - 10.1007/978-3-319-75541-0_2

M3 - Conference contribution

AN - SCOPUS:85044468353

SN - 9783319755403

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

SP - 12

EP - 20

BT - Statistical Atlases and Computational Models of the Heart

A2 - Bernard, Olivier

A2 - Jodoin, Pierre-Marc

A2 - Zhuang, Xiahai

A2 - Yang, Guang

A2 - Young, Alistair

A2 - Sermesant, Maxime

A2 - Lalande, Alain

A2 - Pop, Mihaela

PB - Springer Verlag

T2 - 8th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2017, Held in Conjunction with MICCAI 2017

Y2 - 10 September 2017 through 14 September 2017

ER -

Oksuz I, Dharmakumar R, Tsaftaris SA. Joint myocardial registration and segmentation of cardiac BOLD MRI. In Bernard O, Jodoin PM, Zhuang X, Yang G, Young A, Sermesant M, Lalande A, Pop M, editors, Statistical Atlases and Computational Models of the Heart: ACDC and MMWHS Challenges - 8th International Workshop, STACOM 2017, Revised Selected Papers. Springer Verlag. 2018. p. 12-20. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-75541-0_2

Joint myocardial registration and segmentation of cardiac BOLD MRI

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

Other files and links

Fingerprint

Cite this