A generative model for brain tumor segmentation in multi-modal images

Bjoern H. Menze; Koen Van Leemput; Danial Lashkari; Marc-André Weber; Nicholas Ayache; Polina Golland

doi:10.1007/978-3-642-15745-5_19

A generative model for brain tumor segmentation in multi-modal images

Bjoern H. Menze, Koen Van Leemput, Danial Lashkari, Marc-André Weber, Nicholas Ayache, Polina Golland

Massachusetts Institute of Technology

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

Abstract

We introduce a generative probabilistic model for segmentation of tumors in multi-dimensional images. The model allows for different tumor boundaries in each channel, reflecting difference in tumor appearance across modalities. We augment a probabilistic atlas of healthy tissue priors with a latent atlas of the lesion and derive the estimation algorithm to extract tumor boundaries and the latent atlas from the image data. We present experiments on 25 glioma patient data sets, demonstrating significant improvement over the traditional multivariate tumor segmentation. © 2010 Springer-Verlag.

Original language	English
Title of host publication	Medical Image Computing and Computer-Assisted Intervention
Number of pages	7
Volume	6362
Publisher	Springer-verlag Berlin
Publication date	2010
Pages	151-159
ISBN (Print)	978-3-642-15744-8
DOIs	https://doi.org/10.1007/978-3-642-15745-5_19
Publication status	Published - 2010
Externally published	Yes
Event	13th International Conference on Medical Image Computing and Computer Assisted Intervention - Beijing, China Duration: 20 Sept 2010 → 24 Sept 2010 Conference number: 13 http://www.miccai2010.org/

Conference

Conference	13th International Conference on Medical Image Computing and Computer Assisted Intervention
Number	13
Country/Territory	China
City	Beijing
Period	20/09/2010 → 24/09/2010
Internet address	http://www.miccai2010.org/

Series	Lecture Notes in Computer Science
ISSN	0302-9743

Keywords

Hospital data processing
Medical computing
Medical imaging
Tumors
Image segmentation

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10.1007/978-3-642-15745-5_19

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title = "A generative model for brain tumor segmentation in multi-modal images",

abstract = "We introduce a generative probabilistic model for segmentation of tumors in multi-dimensional images. The model allows for different tumor boundaries in each channel, reflecting difference in tumor appearance across modalities. We augment a probabilistic atlas of healthy tissue priors with a latent atlas of the lesion and derive the estimation algorithm to extract tumor boundaries and the latent atlas from the image data. We present experiments on 25 glioma patient data sets, demonstrating significant improvement over the traditional multivariate tumor segmentation. {\textcopyright} 2010 Springer-Verlag.",

keywords = "Hospital data processing, Medical computing, Medical imaging, Tumors, Image segmentation",

author = "Menze, {Bjoern H.} and {Van Leemput}, Koen and Danial Lashkari and Marc-Andr{\'e} Weber and Nicholas Ayache and Polina Golland",

year = "2010",

doi = "10.1007/978-3-642-15745-5_19",

language = "English",

isbn = "978-3-642-15744-8",

volume = "6362",

series = "Lecture Notes in Computer Science",

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pages = "151--159",

booktitle = "Medical Image Computing and Computer-Assisted Intervention",

note = "13th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI2010 ; Conference date: 20-09-2010 Through 24-09-2010",

url = "http://www.miccai2010.org/",

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Menze, BH, Van Leemput, K, Lashkari, D, Weber, M-A, Ayache, N & Golland, P 2010, A generative model for brain tumor segmentation in multi-modal images. in Medical Image Computing and Computer-Assisted Intervention. vol. 6362, Springer-verlag Berlin, Lecture Notes in Computer Science, pp. 151-159, 13th International Conference on Medical Image Computing and Computer Assisted Intervention, Beijing, China, 20/09/2010. https://doi.org/10.1007/978-3-642-15745-5_19

A generative model for brain tumor segmentation in multi-modal images. / Menze, Bjoern H.; Van Leemput, Koen; Lashkari, Danial et al.
Medical Image Computing and Computer-Assisted Intervention. Vol. 6362 Springer-verlag Berlin, 2010. p. 151-159 (Lecture Notes in Computer Science).

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

TY - GEN

T1 - A generative model for brain tumor segmentation in multi-modal images

AU - Menze, Bjoern H.

AU - Van Leemput, Koen

AU - Lashkari, Danial

AU - Weber, Marc-André

AU - Ayache, Nicholas

AU - Golland, Polina

N1 - Conference code: 13

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N2 - We introduce a generative probabilistic model for segmentation of tumors in multi-dimensional images. The model allows for different tumor boundaries in each channel, reflecting difference in tumor appearance across modalities. We augment a probabilistic atlas of healthy tissue priors with a latent atlas of the lesion and derive the estimation algorithm to extract tumor boundaries and the latent atlas from the image data. We present experiments on 25 glioma patient data sets, demonstrating significant improvement over the traditional multivariate tumor segmentation. © 2010 Springer-Verlag.

AB - We introduce a generative probabilistic model for segmentation of tumors in multi-dimensional images. The model allows for different tumor boundaries in each channel, reflecting difference in tumor appearance across modalities. We augment a probabilistic atlas of healthy tissue priors with a latent atlas of the lesion and derive the estimation algorithm to extract tumor boundaries and the latent atlas from the image data. We present experiments on 25 glioma patient data sets, demonstrating significant improvement over the traditional multivariate tumor segmentation. © 2010 Springer-Verlag.

KW - Hospital data processing

KW - Medical computing

KW - Medical imaging

KW - Tumors

KW - Image segmentation

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DO - 10.1007/978-3-642-15745-5_19

M3 - Article in proceedings

SN - 978-3-642-15744-8

VL - 6362

T3 - Lecture Notes in Computer Science

SP - 151

EP - 159

BT - Medical Image Computing and Computer-Assisted Intervention

PB - Springer-verlag Berlin

T2 - 13th International Conference on Medical Image Computing and Computer Assisted Intervention

Y2 - 20 September 2010 through 24 September 2010

ER -

A generative model for brain tumor segmentation in multi-modal images

Abstract

Conference

Keywords

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