4D Lung Reconstruction with Phase Optimization

Mark Lyksborg; Rasmus Paulsen; Carsten Brink; Rasmus Larsen

doi:10.1007/978-3-642-03882-2

4D Lung Reconstruction with Phase Optimization

Mark Lyksborg, Rasmus Paulsen, Carsten Brink, Rasmus Larsen

Odense University Hospital

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

Abstract

This paper investigates and demonstrates a 4D lung CT reconstruction/registration method which results in a complete volumetric model of the lung that deforms according to a respiratory motion field. The motion field is estimated iteratively between all available slice samples and a reference volume which is updated on the fly. The method is two part and the second part of the method aims to correct wrong phase information by employing another iterative optimizer. This two part iterative optimization allows for complete reconstruction at any phase and it will be demonstrated that it is better than using an optimization which does not correct for phase errors. Knowing how the lung and any tumors located within the lung deforms is relevant in planning the treatment of lung cancer.

Original language	English
Title of host publication	IFMBE Proceedings
Volume	25/4
Place of Publication	Munich
Publisher	Springer Berlin Heidelberg
Publication date	2009
Pages	2227-2230
DOIs	https://doi.org/10.1007/978-3-642-03882-2
Publication status	Published - 2009
Event	World Congress on Medical Physics and Biomedical Engineering - Munich, Germany Duration: 7 Sept 2009 → 12 Sept 2009

Conference

Conference	World Congress on Medical Physics and Biomedical Engineering
Country/Territory	Germany
City	Munich
Period	07/09/2009 → 12/09/2009

Keywords

Motion correction, 4D Lung CT

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/978-3-642-03882-2

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title = "4D Lung Reconstruction with Phase Optimization",

abstract = "This paper investigates and demonstrates a 4D lung CT reconstruction/registration method which results in a complete volumetric model of the lung that deforms according to a respiratory motion field. The motion field is estimated iteratively between all available slice samples and a reference volume which is updated on the fly. The method is two part and the second part of the method aims to correct wrong phase information by employing another iterative optimizer. This two part iterative optimization allows for complete reconstruction at any phase and it will be demonstrated that it is better than using an optimization which does not correct for phase errors. Knowing how the lung and any tumors located within the lung deforms is relevant in planning the treatment of lung cancer.",

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language = "English",

volume = "25/4",

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AU - Lyksborg, Mark

AU - Paulsen, Rasmus

AU - Brink, Carsten

AU - Larsen, Rasmus

PY - 2009

Y1 - 2009

N2 - This paper investigates and demonstrates a 4D lung CT reconstruction/registration method which results in a complete volumetric model of the lung that deforms according to a respiratory motion field. The motion field is estimated iteratively between all available slice samples and a reference volume which is updated on the fly. The method is two part and the second part of the method aims to correct wrong phase information by employing another iterative optimizer. This two part iterative optimization allows for complete reconstruction at any phase and it will be demonstrated that it is better than using an optimization which does not correct for phase errors. Knowing how the lung and any tumors located within the lung deforms is relevant in planning the treatment of lung cancer.

AB - This paper investigates and demonstrates a 4D lung CT reconstruction/registration method which results in a complete volumetric model of the lung that deforms according to a respiratory motion field. The motion field is estimated iteratively between all available slice samples and a reference volume which is updated on the fly. The method is two part and the second part of the method aims to correct wrong phase information by employing another iterative optimizer. This two part iterative optimization allows for complete reconstruction at any phase and it will be demonstrated that it is better than using an optimization which does not correct for phase errors. Knowing how the lung and any tumors located within the lung deforms is relevant in planning the treatment of lung cancer.

KW - Motion correction, 4D Lung CT

U2 - 10.1007/978-3-642-03882-2

DO - 10.1007/978-3-642-03882-2

M3 - Article in proceedings

VL - 25/4

SP - 2227

EP - 2230

BT - IFMBE Proceedings

PB - Springer Berlin Heidelberg

CY - Munich

T2 - World Congress on Medical Physics and Biomedical Engineering

Y2 - 7 September 2009 through 12 September 2009

ER -

4D Lung Reconstruction with Phase Optimization

Abstract

Conference

Keywords

UN SDGs

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