Dictionary learning based image descriptor for myocardial registration of CP-BOLD MR

Ilkay Oksuz; Anirban Mukhopadhyay; Marco Bevilacqua; Rohan Dharmakumar; Sotirios A. Tsaftaris

doi:10.1007/978-3-319-24571-3_25

Dictionary learning based image descriptor for myocardial registration of CP-BOLD MR

Ilkay Oksuz, Anirban Mukhopadhyay, Marco Bevilacqua, Rohan Dharmakumar, Sotirios A. Tsaftaris

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

6 Citations (Scopus)

Abstract

Cardiac Phase-resolved Blood Oxygen-Level-Dependent (CP-BOLD) MRI is a new contrast agent- and stress-free imaging technique for the assessment of myocardial ischemia at rest. The precise registration among the cardiac phases in this cine type acquisition is essential for automating the analysis of images of this technique, since it can potentially lead to better specificity of ischemia detection. However, inconsistency in myocardial intensity patterns and the changes in myocardial shape due to the heart’s motion lead to low registration performance for state-of-the-art methods. This low accuracy can be explained by the lack of distinguishable features in CP-BOLD and inappropriate metric definitions in current intensity-based registration frameworks. In this paper, the sparse representations, which are defined by a discriminative dictionary learning approach for source and target images, are used to improve myocardial registration. This method combines appearance with Gabor and HOG features in a dictionary learning framework to sparsely represent features in a low dimensional space. The sum of absolute differences of these distinctive sparse representations are used to define a similarity term in the registration framework. The proposed approach is validated on a dataset of CP-BOLD MR and standard CINE MR acquired in baseline and ischemic condition across 10 canines.

Original language	English
Title of host publication	Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference, Proceedings
Editors	Joachim Hornegger, Alejandro F. Frangi, William M. Wells, Alejandro F. Frangi, Nassir Navab, Joachim Hornegger, Nassir Navab, William M. Wells, William M. Wells, Alejandro F. Frangi, Joachim Hornegger, Nassir Navab
Publisher	Springer Verlag
Pages	205-213
Number of pages	9
ISBN (Print)	9783319245706, 9783319245706, 9783319245706
DOIs	https://doi.org/10.1007/978-3-319-24571-3_25
Publication status	Published - 2015
Externally published	Yes
Event	18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015 - Munich, Germany Duration: 5 Oct 2015 → 9 Oct 2015

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9350
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015
Country/Territory	Germany
City	Munich
Period	5/10/15 → 9/10/15

Bibliographical note

Publisher Copyright:
© Springer International Publishing Switzerland 2015.

Keywords

CINE MR
CP-BOLD MR
Dictionary Learning
Registration
Similarity Metric

Access to Document

10.1007/978-3-319-24571-3_25

Cite this

Oksuz, I., Mukhopadhyay, A., Bevilacqua, M., Dharmakumar, R., & Tsaftaris, S. A. (2015). Dictionary learning based image descriptor for myocardial registration of CP-BOLD MR. In J. Hornegger, A. F. Frangi, W. M. Wells, A. F. Frangi, N. Navab, J. Hornegger, N. Navab, W. M. Wells, W. M. Wells, A. F. Frangi, J. Hornegger, & N. Navab (Eds.), Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference, Proceedings (pp. 205-213). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9350). Springer Verlag. https://doi.org/10.1007/978-3-319-24571-3_25

Oksuz, Ilkay ; Mukhopadhyay, Anirban ; Bevilacqua, Marco et al. / Dictionary learning based image descriptor for myocardial registration of CP-BOLD MR. Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference, Proceedings. editor / Joachim Hornegger ; Alejandro F. Frangi ; William M. Wells ; Alejandro F. Frangi ; Nassir Navab ; Joachim Hornegger ; Nassir Navab ; William M. Wells ; William M. Wells ; Alejandro F. Frangi ; Joachim Hornegger ; Nassir Navab. Springer Verlag, 2015. pp. 205-213 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Dictionary learning based image descriptor for myocardial registration of CP-BOLD MR",

abstract = "Cardiac Phase-resolved Blood Oxygen-Level-Dependent (CP-BOLD) MRI is a new contrast agent- and stress-free imaging technique for the assessment of myocardial ischemia at rest. The precise registration among the cardiac phases in this cine type acquisition is essential for automating the analysis of images of this technique, since it can potentially lead to better specificity of ischemia detection. However, inconsistency in myocardial intensity patterns and the changes in myocardial shape due to the heart{\textquoteright}s motion lead to low registration performance for state-of-the-art methods. This low accuracy can be explained by the lack of distinguishable features in CP-BOLD and inappropriate metric definitions in current intensity-based registration frameworks. In this paper, the sparse representations, which are defined by a discriminative dictionary learning approach for source and target images, are used to improve myocardial registration. This method combines appearance with Gabor and HOG features in a dictionary learning framework to sparsely represent features in a low dimensional space. The sum of absolute differences of these distinctive sparse representations are used to define a similarity term in the registration framework. The proposed approach is validated on a dataset of CP-BOLD MR and standard CINE MR acquired in baseline and ischemic condition across 10 canines.",

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author = "Ilkay Oksuz and Anirban Mukhopadhyay and Marco Bevilacqua and Rohan Dharmakumar and Tsaftaris, {Sotirios A.}",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015 ; Conference date: 05-10-2015 Through 09-10-2015",

year = "2015",

doi = "10.1007/978-3-319-24571-3_25",

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

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pages = "205--213",

editor = "Joachim Hornegger and Frangi, {Alejandro F.} and Wells, {William M.} and Frangi, {Alejandro F.} and Nassir Navab and Joachim Hornegger and Nassir Navab and Wells, {William M.} and Wells, {William M.} and Frangi, {Alejandro F.} and Joachim Hornegger and Nassir Navab",

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Oksuz, I, Mukhopadhyay, A, Bevilacqua, M, Dharmakumar, R & Tsaftaris, SA 2015, Dictionary learning based image descriptor for myocardial registration of CP-BOLD MR. in J Hornegger, AF Frangi, WM Wells, AF Frangi, N Navab, J Hornegger, N Navab, WM Wells, WM Wells, AF Frangi, J Hornegger & N Navab (eds), Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9350, Springer Verlag, pp. 205-213, 18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015, Munich, Germany, 5/10/15. https://doi.org/10.1007/978-3-319-24571-3_25

Dictionary learning based image descriptor for myocardial registration of CP-BOLD MR. / Oksuz, Ilkay; Mukhopadhyay, Anirban; Bevilacqua, Marco et al.
Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference, Proceedings. ed. / Joachim Hornegger; Alejandro F. Frangi; William M. Wells; Alejandro F. Frangi; Nassir Navab; Joachim Hornegger; Nassir Navab; William M. Wells; William M. Wells; Alejandro F. Frangi; Joachim Hornegger; Nassir Navab. Springer Verlag, 2015. p. 205-213 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9350).

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

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T1 - Dictionary learning based image descriptor for myocardial registration of CP-BOLD MR

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AU - Mukhopadhyay, Anirban

AU - Bevilacqua, Marco

AU - Dharmakumar, Rohan

AU - Tsaftaris, Sotirios A.

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N2 - Cardiac Phase-resolved Blood Oxygen-Level-Dependent (CP-BOLD) MRI is a new contrast agent- and stress-free imaging technique for the assessment of myocardial ischemia at rest. The precise registration among the cardiac phases in this cine type acquisition is essential for automating the analysis of images of this technique, since it can potentially lead to better specificity of ischemia detection. However, inconsistency in myocardial intensity patterns and the changes in myocardial shape due to the heart’s motion lead to low registration performance for state-of-the-art methods. This low accuracy can be explained by the lack of distinguishable features in CP-BOLD and inappropriate metric definitions in current intensity-based registration frameworks. In this paper, the sparse representations, which are defined by a discriminative dictionary learning approach for source and target images, are used to improve myocardial registration. This method combines appearance with Gabor and HOG features in a dictionary learning framework to sparsely represent features in a low dimensional space. The sum of absolute differences of these distinctive sparse representations are used to define a similarity term in the registration framework. The proposed approach is validated on a dataset of CP-BOLD MR and standard CINE MR acquired in baseline and ischemic condition across 10 canines.

AB - Cardiac Phase-resolved Blood Oxygen-Level-Dependent (CP-BOLD) MRI is a new contrast agent- and stress-free imaging technique for the assessment of myocardial ischemia at rest. The precise registration among the cardiac phases in this cine type acquisition is essential for automating the analysis of images of this technique, since it can potentially lead to better specificity of ischemia detection. However, inconsistency in myocardial intensity patterns and the changes in myocardial shape due to the heart’s motion lead to low registration performance for state-of-the-art methods. This low accuracy can be explained by the lack of distinguishable features in CP-BOLD and inappropriate metric definitions in current intensity-based registration frameworks. In this paper, the sparse representations, which are defined by a discriminative dictionary learning approach for source and target images, are used to improve myocardial registration. This method combines appearance with Gabor and HOG features in a dictionary learning framework to sparsely represent features in a low dimensional space. The sum of absolute differences of these distinctive sparse representations are used to define a similarity term in the registration framework. The proposed approach is validated on a dataset of CP-BOLD MR and standard CINE MR acquired in baseline and ischemic condition across 10 canines.

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A2 - Wells, William M.

A2 - Frangi, Alejandro F.

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Oksuz I, Mukhopadhyay A, Bevilacqua M, Dharmakumar R, Tsaftaris SA. Dictionary learning based image descriptor for myocardial registration of CP-BOLD MR. In Hornegger J, Frangi AF, Wells WM, Frangi AF, Navab N, Hornegger J, Navab N, Wells WM, Wells WM, Frangi AF, Hornegger J, Navab N, editors, Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference, Proceedings. Springer Verlag. 2015. p. 205-213. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-24571-3_25

Dictionary learning based image descriptor for myocardial registration of CP-BOLD MR

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Keywords

Access to Document

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