Registration-based segmentation using the information bottleneck method

Anton Bardera; Miquel Feixas; Imma Boada; Jaume Rigau; Mateu Sbert

doi:10.1007/978-3-540-72849-8_17

Registration-based segmentation using the information bottleneck method

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

7 Citations (Scopus)

Abstract

We present two new clustering algorithms for medical image segmentation based on the multimodal image registration and the information bottleneck method. In these algorithms, the histogram bins of two registered multimodal 3D-images are clustered by minimizing the loss of mutual information between them. Thus, the clustering of histogram bins is driven by the preservation of the shared information between the images, extracting from each image the structures that are more relevant to the other one. In the first algorithm, we segment only one image at a time, while in the second both images are simultaneously segmented. Experiments show the good behavior of the presented algorithms, especially the simultaneous clustering.

Original language	English
Title of host publication	Pattern Recognition and Image Analysis - Third Iberian Conference, IbPRIA 2007, Proceedings
Publisher	Springer Verlag
Pages	130-137
Number of pages	8
Edition	PART 2
ISBN (Print)	9783540728481
DOIs	https://doi.org/10.1007/978-3-540-72849-8_17
Publication status	Published - 2007
Event	3rd Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2007 - Girona, Spain Duration: 6 Jun 2007 → 8 Jun 2007

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	4478 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	3rd Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2007
Country/Territory	Spain
City	Girona
Period	6/06/07 → 8/06/07

Access to Document

10.1007/978-3-540-72849-8_17

Cite this

Bardera, A., Feixas, M., Boada, I., Rigau, J., & Sbert, M. (2007). Registration-based segmentation using the information bottleneck method. In Pattern Recognition and Image Analysis - Third Iberian Conference, IbPRIA 2007, Proceedings (PART 2 ed., pp. 130-137). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4478 LNCS, No. PART 2). Springer Verlag. https://doi.org/10.1007/978-3-540-72849-8_17

Bardera, Anton ; Feixas, Miquel ; Boada, Imma et al. / Registration-based segmentation using the information bottleneck method. Pattern Recognition and Image Analysis - Third Iberian Conference, IbPRIA 2007, Proceedings. PART 2. ed. Springer Verlag, 2007. pp. 130-137 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

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title = "Registration-based segmentation using the information bottleneck method",

abstract = "We present two new clustering algorithms for medical image segmentation based on the multimodal image registration and the information bottleneck method. In these algorithms, the histogram bins of two registered multimodal 3D-images are clustered by minimizing the loss of mutual information between them. Thus, the clustering of histogram bins is driven by the preservation of the shared information between the images, extracting from each image the structures that are more relevant to the other one. In the first algorithm, we segment only one image at a time, while in the second both images are simultaneously segmented. Experiments show the good behavior of the presented algorithms, especially the simultaneous clustering.",

author = "Anton Bardera and Miquel Feixas and Imma Boada and Jaume Rigau and Mateu Sbert",

year = "2007",

doi = "10.1007/978-3-540-72849-8\_17",

language = "English",

isbn = "9783540728481",

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

publisher = "Springer Verlag",

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pages = "130--137",

booktitle = "Pattern Recognition and Image Analysis - Third Iberian Conference, IbPRIA 2007, Proceedings",

address = "Germany",

edition = "PART 2",

note = "3rd Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2007 ; Conference date: 06-06-2007 Through 08-06-2007",

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Bardera, A , Feixas, M , Boada, I, Rigau, J & Sbert, M 2007, Registration-based segmentation using the information bottleneck method. in Pattern Recognition and Image Analysis - Third Iberian Conference, IbPRIA 2007, 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. 4478 LNCS, Springer Verlag, pp. 130-137, 3rd Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2007, Girona, Spain, 6/06/07. https://doi.org/10.1007/978-3-540-72849-8_17

Registration-based segmentation using the information bottleneck method. / Bardera, Anton ; Feixas, Miquel ; Boada, Imma et al.
Pattern Recognition and Image Analysis - Third Iberian Conference, IbPRIA 2007, Proceedings. PART 2. ed. Springer Verlag, 2007. p. 130-137 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4478 LNCS, No. PART 2).

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

TY - GEN

T1 - Registration-based segmentation using the information bottleneck method

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AU - Feixas, Miquel

AU - Boada, Imma

AU - Rigau, Jaume

AU - Sbert, Mateu

PY - 2007

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N2 - We present two new clustering algorithms for medical image segmentation based on the multimodal image registration and the information bottleneck method. In these algorithms, the histogram bins of two registered multimodal 3D-images are clustered by minimizing the loss of mutual information between them. Thus, the clustering of histogram bins is driven by the preservation of the shared information between the images, extracting from each image the structures that are more relevant to the other one. In the first algorithm, we segment only one image at a time, while in the second both images are simultaneously segmented. Experiments show the good behavior of the presented algorithms, especially the simultaneous clustering.

AB - We present two new clustering algorithms for medical image segmentation based on the multimodal image registration and the information bottleneck method. In these algorithms, the histogram bins of two registered multimodal 3D-images are clustered by minimizing the loss of mutual information between them. Thus, the clustering of histogram bins is driven by the preservation of the shared information between the images, extracting from each image the structures that are more relevant to the other one. In the first algorithm, we segment only one image at a time, while in the second both images are simultaneously segmented. Experiments show the good behavior of the presented algorithms, especially the simultaneous clustering.

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DO - 10.1007/978-3-540-72849-8_17

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

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BT - Pattern Recognition and Image Analysis - Third Iberian Conference, IbPRIA 2007, Proceedings

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Bardera A , Feixas M , Boada I, Rigau J, Sbert M. Registration-based segmentation using the information bottleneck method. In Pattern Recognition and Image Analysis - Third Iberian Conference, IbPRIA 2007, Proceedings. PART 2 ed. Springer Verlag. 2007. p. 130-137. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-540-72849-8_17

Registration-based segmentation using the information bottleneck method

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