Conditional random fields for object and background estimation in fluorescence video-microscopy

T. Pécot; A. Chessel; S. Bardin; J. Salamero; P. Bouthemy; C. Kervrann

doi:10.1109/ISBI.2009.5193152

Conditional random fields for object and background estimation in fluorescence video-microscopy

T. Pécot
, A. Chessel
, S. Bardin
, J. Salamero
, P. Bouthemy
, C. Kervrann

INRIA Institut National de Recherche en Informatique et en Automatique
UR341 Mathématiques et Informatique Appliquées
Institut Curie
CNRS UMR144

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

Abstract

This paper describes an original method to detect XFP-tagged proteins in time-lapse microscopy. Non-local measurements able to capture spatial intensity variations are incorporated within a Conditional Random Field (CRF) framework to localize the objects of interest. The minimization of the related energy is performed by a min-cut/max-flow algorithm. Furthermore, we estimate the slowly varying background at each time step. The difference between the current image and the estimated background provides new and reliable measurements for object detection. Experimental results on simulated and real data demonstrate the performance of the proposed method.

Original language	English
Title of host publication	Proceedings - 2009 IEEE International Symposium on Biomedical Imaging
Subtitle of host publication	From Nano to Macro, ISBI 2009
Publisher	IEEE Computer Society
Pages	734-737
Number of pages	4
ISBN (Print)	9781424439324
DOIs	https://doi.org/10.1109/ISBI.2009.5193152
Publication status	Published - 1 Jan 2009
Event	6th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009 - Boston, MA, United States Duration: 28 Jun 2009 → 1 Jul 2009

Publication series

Name	Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009

Conference

Conference	6th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009
Country/Territory	United States
City	Boston, MA
Period	28/06/09 → 1/07/09

Keywords

Biomedical microscopy
Conditional random fields
Fluorescence
Min-cut/max-flow minimization
Object detection

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10.1109/ISBI.2009.5193152

Cite this

Pécot, T., Chessel, A., Bardin, S., Salamero, J., Bouthemy, P., & Kervrann, C. (2009). Conditional random fields for object and background estimation in fluorescence video-microscopy. In Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009 (pp. 734-737). Article 5193152 (Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009). IEEE Computer Society. https://doi.org/10.1109/ISBI.2009.5193152

Pécot, T. ; Chessel, A. ; Bardin, S. et al. / Conditional random fields for object and background estimation in fluorescence video-microscopy. Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009. IEEE Computer Society, 2009. pp. 734-737 (Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009).

@inproceedings{bde094090fe94d73b9ec381e53a138de,

title = "Conditional random fields for object and background estimation in fluorescence video-microscopy",

abstract = "This paper describes an original method to detect XFP-tagged proteins in time-lapse microscopy. Non-local measurements able to capture spatial intensity variations are incorporated within a Conditional Random Field (CRF) framework to localize the objects of interest. The minimization of the related energy is performed by a min-cut/max-flow algorithm. Furthermore, we estimate the slowly varying background at each time step. The difference between the current image and the estimated background provides new and reliable measurements for object detection. Experimental results on simulated and real data demonstrate the performance of the proposed method.",

keywords = "Biomedical microscopy, Conditional random fields, Fluorescence, Min-cut/max-flow minimization, Object detection",

author = "T. P{\'e}cot and A. Chessel and S. Bardin and J. Salamero and P. Bouthemy and C. Kervrann",

year = "2009",

month = jan,

day = "1",

doi = "10.1109/ISBI.2009.5193152",

language = "English",

isbn = "9781424439324",

series = "Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009",

publisher = "IEEE Computer Society",

pages = "734--737",

booktitle = "Proceedings - 2009 IEEE International Symposium on Biomedical Imaging",

note = "6th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009 ; Conference date: 28-06-2009 Through 01-07-2009",

}

Pécot, T, Chessel, A, Bardin, S, Salamero, J, Bouthemy, P & Kervrann, C 2009, Conditional random fields for object and background estimation in fluorescence video-microscopy. in Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009., 5193152, Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009, IEEE Computer Society, pp. 734-737, 6th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009, Boston, MA, United States, 28/06/09. https://doi.org/10.1109/ISBI.2009.5193152

Conditional random fields for object and background estimation in fluorescence video-microscopy. / Pécot, T.; Chessel, A.; Bardin, S. et al.
Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009. IEEE Computer Society, 2009. p. 734-737 5193152 (Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009).

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

TY - GEN

T1 - Conditional random fields for object and background estimation in fluorescence video-microscopy

AU - Pécot, T.

AU - Chessel, A.

AU - Bardin, S.

AU - Salamero, J.

AU - Bouthemy, P.

AU - Kervrann, C.

PY - 2009/1/1

Y1 - 2009/1/1

N2 - This paper describes an original method to detect XFP-tagged proteins in time-lapse microscopy. Non-local measurements able to capture spatial intensity variations are incorporated within a Conditional Random Field (CRF) framework to localize the objects of interest. The minimization of the related energy is performed by a min-cut/max-flow algorithm. Furthermore, we estimate the slowly varying background at each time step. The difference between the current image and the estimated background provides new and reliable measurements for object detection. Experimental results on simulated and real data demonstrate the performance of the proposed method.

AB - This paper describes an original method to detect XFP-tagged proteins in time-lapse microscopy. Non-local measurements able to capture spatial intensity variations are incorporated within a Conditional Random Field (CRF) framework to localize the objects of interest. The minimization of the related energy is performed by a min-cut/max-flow algorithm. Furthermore, we estimate the slowly varying background at each time step. The difference between the current image and the estimated background provides new and reliable measurements for object detection. Experimental results on simulated and real data demonstrate the performance of the proposed method.

KW - Biomedical microscopy

KW - Conditional random fields

KW - Fluorescence

KW - Min-cut/max-flow minimization

KW - Object detection

U2 - 10.1109/ISBI.2009.5193152

DO - 10.1109/ISBI.2009.5193152

M3 - Conference contribution

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SN - 9781424439324

T3 - Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009

SP - 734

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BT - Proceedings - 2009 IEEE International Symposium on Biomedical Imaging

PB - IEEE Computer Society

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ER -

Pécot T, Chessel A, Bardin S, Salamero J, Bouthemy P, Kervrann C. Conditional random fields for object and background estimation in fluorescence video-microscopy. In Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009. IEEE Computer Society. 2009. p. 734-737. 5193152. (Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009). doi: 10.1109/ISBI.2009.5193152

Conditional random fields for object and background estimation in fluorescence video-microscopy

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Keywords

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