A dynamic image reconstruction method with spatio-temporal constraints

Hyun Keol Kim; Michael Khahil; Jacqueline Gunther; Ludguier Montejo; Andreas H. Hielscher

doi:10.1117/12.2003394

A dynamic image reconstruction method with spatio-temporal constraints

Hyun Keol Kim, Michael Khahil, Jacqueline Gunther, Ludguier Montejo, Andreas H. Hielscher

Biomedical Engineering

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

Abstract

We introduce here a temporally constrained image reconstruction algorithm for fast dynamic imaging of the spatial distribution of tissue parameters such as oxy-hemoglobin, HbO2, or deoxy-hemoglobin, Hb, and their derived parameters, e.g., HbT or StO2. An unknown spatial-temporal distribution of the tissue parameter is represented by a combination of basis functions where bases are predefined and their coefficients are unknown. The performance of the new algorithm is evaluated using experimental studies with dynamic imaging of vascular disease in foot. The results show that the temporally constrained algorithm leads to 26- fold acceleration in the image reconstruction as compared to more traditional methods that have to reconstruct all time frames data sequentially.

Original language	English (US)
Title of host publication	Photons Plus Ultrasound
Subtitle of host publication	Imaging and Sensing 2013
DOIs	https://doi.org/10.1117/12.2003394
State	Published - 2013
Event	Photons Plus Ultrasound: Imaging and Sensing 2013 - San Francisco, CA, United States Duration: Feb 3 2013 → Feb 5 2013

Publication series

Name	Progress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume	8581
ISSN (Print)	1605-7422

Conference

Conference	Photons Plus Ultrasound: Imaging and Sensing 2013
Country/Territory	United States
City	San Francisco, CA
Period	2/3/13 → 2/5/13

Keywords

PDE-constrained
Temporally-constrained
dynamic image reconstruction

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Atomic and Molecular Physics, and Optics
Radiology Nuclear Medicine and imaging
Biomaterials

Access to Document

10.1117/12.2003394

Cite this

Kim, HK, Khahil, M, Gunther, J, Montejo, L & Hielscher, AH 2013, A dynamic image reconstruction method with spatio-temporal constraints. in Photons Plus Ultrasound: Imaging and Sensing 2013., 858131, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 8581, Photons Plus Ultrasound: Imaging and Sensing 2013, San Francisco, CA, United States, 2/3/13. https://doi.org/10.1117/12.2003394

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title = "A dynamic image reconstruction method with spatio-temporal constraints",

abstract = "We introduce here a temporally constrained image reconstruction algorithm for fast dynamic imaging of the spatial distribution of tissue parameters such as oxy-hemoglobin, HbO2, or deoxy-hemoglobin, Hb, and their derived parameters, e.g., HbT or StO2. An unknown spatial-temporal distribution of the tissue parameter is represented by a combination of basis functions where bases are predefined and their coefficients are unknown. The performance of the new algorithm is evaluated using experimental studies with dynamic imaging of vascular disease in foot. The results show that the temporally constrained algorithm leads to 26- fold acceleration in the image reconstruction as compared to more traditional methods that have to reconstruct all time frames data sequentially.",

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author = "Kim, {Hyun Keol} and Michael Khahil and Jacqueline Gunther and Ludguier Montejo and Hielscher, {Andreas H.}",

year = "2013",

doi = "10.1117/12.2003394",

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AU - Kim, Hyun Keol

AU - Khahil, Michael

AU - Gunther, Jacqueline

AU - Montejo, Ludguier

AU - Hielscher, Andreas H.

PY - 2013

Y1 - 2013

N2 - We introduce here a temporally constrained image reconstruction algorithm for fast dynamic imaging of the spatial distribution of tissue parameters such as oxy-hemoglobin, HbO2, or deoxy-hemoglobin, Hb, and their derived parameters, e.g., HbT or StO2. An unknown spatial-temporal distribution of the tissue parameter is represented by a combination of basis functions where bases are predefined and their coefficients are unknown. The performance of the new algorithm is evaluated using experimental studies with dynamic imaging of vascular disease in foot. The results show that the temporally constrained algorithm leads to 26- fold acceleration in the image reconstruction as compared to more traditional methods that have to reconstruct all time frames data sequentially.

AB - We introduce here a temporally constrained image reconstruction algorithm for fast dynamic imaging of the spatial distribution of tissue parameters such as oxy-hemoglobin, HbO2, or deoxy-hemoglobin, Hb, and their derived parameters, e.g., HbT or StO2. An unknown spatial-temporal distribution of the tissue parameter is represented by a combination of basis functions where bases are predefined and their coefficients are unknown. The performance of the new algorithm is evaluated using experimental studies with dynamic imaging of vascular disease in foot. The results show that the temporally constrained algorithm leads to 26- fold acceleration in the image reconstruction as compared to more traditional methods that have to reconstruct all time frames data sequentially.

KW - PDE-constrained

KW - Temporally-constrained

KW - dynamic image reconstruction

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M3 - Conference contribution

AN - SCOPUS:84878089339

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T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE

BT - Photons Plus Ultrasound

T2 - Photons Plus Ultrasound: Imaging and Sensing 2013

Y2 - 3 February 2013 through 5 February 2013

ER -

A dynamic image reconstruction method with spatio-temporal constraints

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

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