New partial volume estimation methods for MRI MP2RAGE

Quentin Duché; Parnesh Raniga; Gary F. Egan; Oscar Acosta; Giulio Gambarota; Olivier Salvado; Hervé Saint-Jalmes

doi:10.1007/978-3-319-10443-0_17

New partial volume estimation methods for MRI MP2RAGE

Quentin Duché, Parnesh Raniga, Gary F. Egan, Oscar Acosta, Giulio Gambarota, Olivier Salvado, Hervé Saint-Jalmes

Monash Biomedical Imaging

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

4 Citations (Scopus)

Abstract

Magnetic resonance imaging (MRI) is commonly used as a medical diagnosis tool, especially for brain applications. Some limitations affecting image quality include receive field (RF) inhomogeneity and partial volume (PV) effects which arise when a voxel contains two different tissues, introducing blurring. The novel Magnetization-Prepared 2 Rapid Acquisition Gradient Echoes (MP2RAGE) provides an image robust to RF inhomogeneity. However, PV effects are still an issue for automated brain quantification. PV estimation methods have been proposed based on computing the proportion of one tissue with respect to the other using linear interpolation of pure tissue intensity means. We demonstrated that this linear model introduces bias when used with MP2RAGE and we propose two novel solutions. The PV estimation methods were tested on 4 MP2RAGE data sets.

Original language	English
Title of host publication	Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - 17th International Conference, Proceedings
Publisher	Springer-Verlag London Ltd.
Pages	129-136
Number of pages	8
Volume	8675 LNCS
Edition	PART 3
ISBN (Print)	9783319104423
DOIs	https://doi.org/10.1007/978-3-319-10443-0_17
Publication status	Published - 2014
Event	Medical Image Computing and Computer-Assisted Intervention 2014 - Massachusetts Institute of Technology (MIT) and Harvard Medical School , Boston, United States of America Duration: 14 Sep 2014 → 18 Sep 2014 Conference number: 17th

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 3
Volume	8675 LNCS
ISSN (Print)	03029743
ISSN (Electronic)	16113349

Conference

Conference	Medical Image Computing and Computer-Assisted Intervention 2014
Abbreviated title	MICCAI 2014
Country	United States of America
City	Boston
Period	14/09/14 → 18/09/14

Keywords

Bi-exponential model
MP2RAGE
Partial Volume Estimation

Access to Document

10.1007/978-3-319-10443-0_17

Link to publication in Scopus

Cite this

Duché, Q., Raniga, P., Egan, G. F., Acosta, O., Gambarota, G., Salvado, O., & Saint-Jalmes, H. (2014). New partial volume estimation methods for MRI MP2RAGE. In Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - 17th International Conference, Proceedings (PART 3 ed., Vol. 8675 LNCS, pp. 129-136). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8675 LNCS, No. PART 3). Springer-Verlag London Ltd.. https://doi.org/10.1007/978-3-319-10443-0_17

Duché, Quentin ; Raniga, Parnesh ; Egan, Gary F. ; Acosta, Oscar ; Gambarota, Giulio ; Salvado, Olivier ; Saint-Jalmes, Hervé. / New partial volume estimation methods for MRI MP2RAGE. Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - 17th International Conference, Proceedings. Vol. 8675 LNCS PART 3. ed. Springer-Verlag London Ltd., 2014. pp. 129-136 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3).

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abstract = "Magnetic resonance imaging (MRI) is commonly used as a medical diagnosis tool, especially for brain applications. Some limitations affecting image quality include receive field (RF) inhomogeneity and partial volume (PV) effects which arise when a voxel contains two different tissues, introducing blurring. The novel Magnetization-Prepared 2 Rapid Acquisition Gradient Echoes (MP2RAGE) provides an image robust to RF inhomogeneity. However, PV effects are still an issue for automated brain quantification. PV estimation methods have been proposed based on computing the proportion of one tissue with respect to the other using linear interpolation of pure tissue intensity means. We demonstrated that this linear model introduces bias when used with MP2RAGE and we propose two novel solutions. The PV estimation methods were tested on 4 MP2RAGE data sets.",

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Duché, Q, Raniga, P, Egan, GF, Acosta, O, Gambarota, G, Salvado, O & Saint-Jalmes, H 2014, New partial volume estimation methods for MRI MP2RAGE. in Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - 17th International Conference, Proceedings. PART 3 edn, vol. 8675 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 3, vol. 8675 LNCS, Springer-Verlag London Ltd., pp. 129-136, Medical Image Computing and Computer-Assisted Intervention 2014, Boston, United States of America, 14/09/14. https://doi.org/10.1007/978-3-319-10443-0_17

New partial volume estimation methods for MRI MP2RAGE. / Duché, Quentin; Raniga, Parnesh; Egan, Gary F.; Acosta, Oscar; Gambarota, Giulio; Salvado, Olivier; Saint-Jalmes, Hervé.

Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - 17th International Conference, Proceedings. Vol. 8675 LNCS PART 3. ed. Springer-Verlag London Ltd., 2014. p. 129-136 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8675 LNCS, No. PART 3).

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

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Duché Q, Raniga P, Egan GF, Acosta O, Gambarota G, Salvado O et al. New partial volume estimation methods for MRI MP2RAGE. In Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - 17th International Conference, Proceedings. PART 3 ed. Vol. 8675 LNCS. Springer-Verlag London Ltd. 2014. p. 129-136. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3). https://doi.org/10.1007/978-3-319-10443-0_17