Improved sparse reconstruction for fluorescence molecular tomography with Poisson noise modeling

Yansong Zhu; Abhinav K. Jha; Dean F. Wong; Arman Rahmim

doi:10.1364/TRANSLATIONAL.2018.JTu3A.51

Improved sparse reconstruction for fluorescence molecular tomography with Poisson noise modeling

Yansong Zhu, Abhinav K. Jha, Dean F. Wong, Arman Rahmim

School of Medicine

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

1 Scopus citations

Abstract

We present a maximum-likelihood-expectation-maximization (MLEM)-based method that models Poisson noise for improved reconstruction in fluoroscence molecular tomography with sparse fluroscence distribution.

Original language	English (US)
Title of host publication	Clinical and Translational Biophotonics, TRANSLATIONAL 2018
Publisher	Optica Publishing Group (formerly OSA)
ISBN (Print)	9781943580415
DOIs	https://doi.org/10.1364/TRANSLATIONAL.2018.JTu3A.51
State	Published - 2018
Event	Clinical and Translational Biophotonics, TRANSLATIONAL 2018 - Hollywood, United States Duration: Apr 3 2018 → Apr 6 2018

Publication series

Name	Optics InfoBase Conference Papers
Volume	Part F91-TRANSLATIONAL 2018
ISSN (Electronic)	2162-2701

Other

Other	Clinical and Translational Biophotonics, TRANSLATIONAL 2018
Country/Territory	United States
City	Hollywood
Period	4/3/18 → 4/6/18

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Mechanics of Materials

Access to Document

10.1364/TRANSLATIONAL.2018.JTu3A.51

Cite this

Zhu, Y., Jha, A. K., Wong, D. F., & Rahmim, A. (2018). Improved sparse reconstruction for fluorescence molecular tomography with Poisson noise modeling. In Clinical and Translational Biophotonics, TRANSLATIONAL 2018 (Optics InfoBase Conference Papers; Vol. Part F91-TRANSLATIONAL 2018). Optica Publishing Group (formerly OSA). https://doi.org/10.1364/TRANSLATIONAL.2018.JTu3A.51

Improved sparse reconstruction for fluorescence molecular tomography with Poisson noise modeling. / Zhu, Yansong; Jha, Abhinav K.; Wong, Dean F. et al.
Clinical and Translational Biophotonics, TRANSLATIONAL 2018. Optica Publishing Group (formerly OSA), 2018. (Optics InfoBase Conference Papers; Vol. Part F91-TRANSLATIONAL 2018).

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

Zhu, Y, Jha, AK, Wong, DF & Rahmim, A 2018, Improved sparse reconstruction for fluorescence molecular tomography with Poisson noise modeling. in Clinical and Translational Biophotonics, TRANSLATIONAL 2018. Optics InfoBase Conference Papers, vol. Part F91-TRANSLATIONAL 2018, Optica Publishing Group (formerly OSA), Clinical and Translational Biophotonics, TRANSLATIONAL 2018, Hollywood, United States, 4/3/18. https://doi.org/10.1364/TRANSLATIONAL.2018.JTu3A.51

@inproceedings{7680d8e03dc044b6b0c94c4f37a9d752,

title = "Improved sparse reconstruction for fluorescence molecular tomography with Poisson noise modeling",

abstract = "We present a maximum-likelihood-expectation-maximization (MLEM)-based method that models Poisson noise for improved reconstruction in fluoroscence molecular tomography with sparse fluroscence distribution.",

author = "Yansong Zhu and Jha, {Abhinav K.} and Wong, {Dean F.} and Arman Rahmim",

note = "Publisher Copyright: {\textcopyright} OSA 2018.; Clinical and Translational Biophotonics, TRANSLATIONAL 2018 ; Conference date: 03-04-2018 Through 06-04-2018",

year = "2018",

doi = "10.1364/TRANSLATIONAL.2018.JTu3A.51",

language = "English (US)",

isbn = "9781943580415",

series = "Optics InfoBase Conference Papers",

publisher = "Optica Publishing Group (formerly OSA)",

booktitle = "Clinical and Translational Biophotonics, TRANSLATIONAL 2018",

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AU - Zhu, Yansong

AU - Jha, Abhinav K.

AU - Wong, Dean F.

AU - Rahmim, Arman

PY - 2018

Y1 - 2018

N2 - We present a maximum-likelihood-expectation-maximization (MLEM)-based method that models Poisson noise for improved reconstruction in fluoroscence molecular tomography with sparse fluroscence distribution.

AB - We present a maximum-likelihood-expectation-maximization (MLEM)-based method that models Poisson noise for improved reconstruction in fluoroscence molecular tomography with sparse fluroscence distribution.

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U2 - 10.1364/TRANSLATIONAL.2018.JTu3A.51

DO - 10.1364/TRANSLATIONAL.2018.JTu3A.51

M3 - Conference contribution

AN - SCOPUS:85047528720

SN - 9781943580415

T3 - Optics InfoBase Conference Papers

BT - Clinical and Translational Biophotonics, TRANSLATIONAL 2018

PB - Optica Publishing Group (formerly OSA)

T2 - Clinical and Translational Biophotonics, TRANSLATIONAL 2018

Y2 - 3 April 2018 through 6 April 2018

ER -

Improved sparse reconstruction for fluorescence molecular tomography with Poisson noise modeling

Abstract

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ASJC Scopus subject areas

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