3D PET-driven multi-phase segmentation of meningiomas in MRI

H. Urien; I. Buvat; N. Rougon; S. Boughdad; I. Block

doi:10.1109/ISBI.2016.7493294

3D PET-driven multi-phase segmentation of meningiomas in MRI

H. Urien
, I. Buvat
, N. Rougon
, S. Boughdad
, I. Block

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

Abstract

Combining anatomical and functional information from Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) scans brings great opportunities to improve diagnosis in oncology and treatment planning in radiation oncology. In this work, we propose a PET-guided MR tumor segmentation method minimizing a globally convex energy in a multiphase framework to account for the context variability of lesions. The method was evaluated in four patients with atypical meningiomas of different shapes, locations and metabolism, and the Dice index obtained by comparing with a manual tumor segmentation performed by an expert was 0.65 ± 0.13. The results demonstrated a good ability of the method to differentiate tumors from tissues with similar MRI intensity values.

Original language	English
Title of host publication	2016 IEEE International Symposium on Biomedical Imaging
Subtitle of host publication	From Nano to Macro, ISBI 2016 - Proceedings
Publisher	IEEE Computer Society
Pages	407-410
Number of pages	4
ISBN (Electronic)	9781479923502
DOIs	https://doi.org/10.1109/ISBI.2016.7493294
Publication status	Published - 15 Jun 2016
Externally published	Yes
Event	13th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Prague, Czech Republic Duration: 13 Apr 2016 → 16 Apr 2016

Publication series

Name	Proceedings - International Symposium on Biomedical Imaging
Volume	2016-June
ISSN (Print)	1945-7928
ISSN (Electronic)	1945-8452

Conference

Conference	13th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016
Country/Territory	Czech Republic
City	Prague
Period	13/04/16 → 16/04/16

Keywords

Brain Tumor
Magnetic Resonance Imaging (MRI)
Multimodal segmentation
Positron Emission Tomography (PET)
variational method

Access to Document

10.1109/ISBI.2016.7493294

Cite this

Urien, H., Buvat, I., Rougon, N., Boughdad, S., & Block, I. (2016). 3D PET-driven multi-phase segmentation of meningiomas in MRI. In 2016 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Proceedings (pp. 407-410). Article 7493294 (Proceedings - International Symposium on Biomedical Imaging; Vol. 2016-June). IEEE Computer Society. https://doi.org/10.1109/ISBI.2016.7493294

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title = "3D PET-driven multi-phase segmentation of meningiomas in MRI",

abstract = "Combining anatomical and functional information from Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) scans brings great opportunities to improve diagnosis in oncology and treatment planning in radiation oncology. In this work, we propose a PET-guided MR tumor segmentation method minimizing a globally convex energy in a multiphase framework to account for the context variability of lesions. The method was evaluated in four patients with atypical meningiomas of different shapes, locations and metabolism, and the Dice index obtained by comparing with a manual tumor segmentation performed by an expert was 0.65 ± 0.13. The results demonstrated a good ability of the method to differentiate tumors from tissues with similar MRI intensity values.",

keywords = "Brain Tumor, Magnetic Resonance Imaging (MRI), Multimodal segmentation, Positron Emission Tomography (PET), variational method",

author = "H. Urien and I. Buvat and N. Rougon and S. Boughdad and I. Block",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 13th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 ; Conference date: 13-04-2016 Through 16-04-2016",

year = "2016",

month = jun,

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doi = "10.1109/ISBI.2016.7493294",

language = "English",

series = "Proceedings - International Symposium on Biomedical Imaging",

publisher = "IEEE Computer Society",

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Urien, H, Buvat, I, Rougon, N, Boughdad, S & Block, I 2016, 3D PET-driven multi-phase segmentation of meningiomas in MRI. in 2016 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Proceedings., 7493294, Proceedings - International Symposium on Biomedical Imaging, vol. 2016-June, IEEE Computer Society, pp. 407-410, 13th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016, Prague, Czech Republic, 13/04/16. https://doi.org/10.1109/ISBI.2016.7493294

3D PET-driven multi-phase segmentation of meningiomas in MRI. / Urien, H.; Buvat, I.; Rougon, N. et al.
2016 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Proceedings. IEEE Computer Society, 2016. p. 407-410 7493294 (Proceedings - International Symposium on Biomedical Imaging; Vol. 2016-June).

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

TY - GEN

T1 - 3D PET-driven multi-phase segmentation of meningiomas in MRI

AU - Urien, H.

AU - Buvat, I.

AU - Rougon, N.

AU - Boughdad, S.

AU - Block, I.

PY - 2016/6/15

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N2 - Combining anatomical and functional information from Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) scans brings great opportunities to improve diagnosis in oncology and treatment planning in radiation oncology. In this work, we propose a PET-guided MR tumor segmentation method minimizing a globally convex energy in a multiphase framework to account for the context variability of lesions. The method was evaluated in four patients with atypical meningiomas of different shapes, locations and metabolism, and the Dice index obtained by comparing with a manual tumor segmentation performed by an expert was 0.65 ± 0.13. The results demonstrated a good ability of the method to differentiate tumors from tissues with similar MRI intensity values.

AB - Combining anatomical and functional information from Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) scans brings great opportunities to improve diagnosis in oncology and treatment planning in radiation oncology. In this work, we propose a PET-guided MR tumor segmentation method minimizing a globally convex energy in a multiphase framework to account for the context variability of lesions. The method was evaluated in four patients with atypical meningiomas of different shapes, locations and metabolism, and the Dice index obtained by comparing with a manual tumor segmentation performed by an expert was 0.65 ± 0.13. The results demonstrated a good ability of the method to differentiate tumors from tissues with similar MRI intensity values.

KW - Brain Tumor

KW - Magnetic Resonance Imaging (MRI)

KW - Multimodal segmentation

KW - Positron Emission Tomography (PET)

KW - variational method

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M3 - Conference contribution

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Y2 - 13 April 2016 through 16 April 2016

ER -

3D PET-driven multi-phase segmentation of meningiomas in MRI

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Keywords

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