Extracting brain regions from rest fMRI with total-variation constrained dictionary learning

Alexandre Abraham; Elvis Dohmatob; Bertrand Thirion; Dimitris Samaras; Gael Varoquaux

doi:10.1007/978-3-642-40763-5_75

Extracting brain regions from rest fMRI with total-variation constrained dictionary learning

Alexandre Abraham
, Elvis Dohmatob
, Bertrand Thirion
, Dimitris Samaras
, Gael Varoquaux

Computer Science

Institut national de recherche en informatique et en automatique
Commissariat à l’énergie atomique et aux énergies alternatives

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

38 Scopus citations

Abstract

Spontaneous brain activity reveals mechanisms of brain function and dysfunction. Its population-level statistical analysis based on functional images often relies on the definition of brain regions that must summarize efficiently the covariance structure between the multiple brain networks. In this paper, we extend a network-discovery approach, namely dictionary learning, to readily extract brain regions. To do so, we introduce a new tool drawing from clustering and linear decomposition methods by carefully crafting a penalty. Our approach automatically extracts regions from rest fMRI that better explain the data and are more stable across subjects than reference decomposition or clustering methods.

Original language	English
Title of host publication	Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013 - 16th International Conference, Proceedings
Pages	607-615
Number of pages	9
Edition	PART 2
DOIs	https://doi.org/10.1007/978-3-642-40763-5_75
State	Published - 2013
Event	16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013 - Nagoya, Japan Duration: Sep 22 2013 → Sep 26 2013

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	8150 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013
Country/Territory	Japan
City	Nagoya
Period	09/22/13 → 09/26/13

Keywords

clustering
dictionary learning
resting state fMRI

Access to Document

10.1007/978-3-642-40763-5_75

Cite this

Abraham, A., Dohmatob, E., Thirion, B., Samaras, D., & Varoquaux, G. (2013). Extracting brain regions from rest fMRI with total-variation constrained dictionary learning. In Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013 - 16th International Conference, Proceedings (PART 2 ed., pp. 607-615). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8150 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-40763-5_75

Abraham, Alexandre ; Dohmatob, Elvis ; Thirion, Bertrand et al. / Extracting brain regions from rest fMRI with total-variation constrained dictionary learning. Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013 - 16th International Conference, Proceedings. PART 2. ed. 2013. pp. 607-615 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

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abstract = "Spontaneous brain activity reveals mechanisms of brain function and dysfunction. Its population-level statistical analysis based on functional images often relies on the definition of brain regions that must summarize efficiently the covariance structure between the multiple brain networks. In this paper, we extend a network-discovery approach, namely dictionary learning, to readily extract brain regions. To do so, we introduce a new tool drawing from clustering and linear decomposition methods by carefully crafting a penalty. Our approach automatically extracts regions from rest fMRI that better explain the data and are more stable across subjects than reference decomposition or clustering methods.",

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Abraham, A, Dohmatob, E, Thirion, B, Samaras, D & Varoquaux, G 2013, Extracting brain regions from rest fMRI with total-variation constrained dictionary learning. in Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013 - 16th International Conference, Proceedings. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 8150 LNCS, pp. 607-615, 16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013, Nagoya, Japan, 09/22/13. https://doi.org/10.1007/978-3-642-40763-5_75

Extracting brain regions from rest fMRI with total-variation constrained dictionary learning. / Abraham, Alexandre; Dohmatob, Elvis; Thirion, Bertrand et al.
Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013 - 16th International Conference, Proceedings. PART 2. ed. 2013. p. 607-615 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8150 LNCS, No. PART 2).

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

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PY - 2013

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Abraham A, Dohmatob E, Thirion B, Samaras D, Varoquaux G. Extracting brain regions from rest fMRI with total-variation constrained dictionary learning. In Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013 - 16th International Conference, Proceedings. PART 2 ed. 2013. p. 607-615. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-642-40763-5_75

Extracting brain regions from rest fMRI with total-variation constrained dictionary learning

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Keywords

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