Appearance based Spatiotemporal Constraint for LV Segmentation in 4D Cardiac SPECT

Yang Ronghua; Majid Mirmehdi; Xie Xianghua; Hall David

Appearance based Spatiotemporal Constraint for LV Segmentation in 4D Cardiac SPECT

Yang Ronghua, Majid Mirmehdi, Xie Xianghua, Hall David

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

Abstract

We propose a novel appearance based spatiotemporal constraint and combine it with a level set based deformable model, which can be used for Left Ventricle segmentation in 4D gated cardiac SPECT, particularly in the presence of perfusion defects. Unlike current shape based constraint works, ours incorporates texture in addition to shape information into a probabilistic constraint, and utilizes spatiotemporal regularization via a Maximum A Posteriori framework. We present comparative results to illustrate the improvement gain.

Translated title of the contribution	Appearance based Spatiotemporal Constraint for LV Segmentation in 4D Cardiac SPECT
Original language	English
Title of host publication	MICCAI Workshop on Cardiovascular Intervetional Imaging and Biophysical Modelling
Publication status	Published - 2009

Bibliographical note

Other page information: 84-93
Conference Proceedings/Title of Journal: MICCAI Workshop on Cardiovascular Intervetional Imaging and Biophysical Modelling
Other identifier: 2001036

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@inproceedings{1ba5c487d9c049459d7ee9c18369cc74,

title = "Appearance based Spatiotemporal Constraint for LV Segmentation in 4D Cardiac SPECT",

abstract = "We propose a novel appearance based spatiotemporal constraint and combine it with a level set based deformable model, which can be used for Left Ventricle segmentation in 4D gated cardiac SPECT, particularly in the presence of perfusion defects. Unlike current shape based constraint works, ours incorporates texture in addition to shape information into a probabilistic constraint, and utilizes spatiotemporal regularization via a Maximum A Posteriori framework. We present comparative results to illustrate the improvement gain. ",

author = "Yang Ronghua and Majid Mirmehdi and Xie Xianghua and Hall David",

note = "Other page information: 84-93 Conference Proceedings/Title of Journal: MICCAI Workshop on Cardiovascular Intervetional Imaging and Biophysical Modelling Other identifier: 2001036",

year = "2009",

language = "English",

booktitle = "MICCAI Workshop on Cardiovascular Intervetional Imaging and Biophysical Modelling",

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TY - GEN

T1 - Appearance based Spatiotemporal Constraint for LV Segmentation in 4D Cardiac SPECT

AU - Ronghua, Yang

AU - Mirmehdi, Majid

AU - Xianghua, Xie

AU - David, Hall

N1 - Other page information: 84-93 Conference Proceedings/Title of Journal: MICCAI Workshop on Cardiovascular Intervetional Imaging and Biophysical Modelling Other identifier: 2001036

PY - 2009

Y1 - 2009

N2 - We propose a novel appearance based spatiotemporal constraint and combine it with a level set based deformable model, which can be used for Left Ventricle segmentation in 4D gated cardiac SPECT, particularly in the presence of perfusion defects. Unlike current shape based constraint works, ours incorporates texture in addition to shape information into a probabilistic constraint, and utilizes spatiotemporal regularization via a Maximum A Posteriori framework. We present comparative results to illustrate the improvement gain.

AB - We propose a novel appearance based spatiotemporal constraint and combine it with a level set based deformable model, which can be used for Left Ventricle segmentation in 4D gated cardiac SPECT, particularly in the presence of perfusion defects. Unlike current shape based constraint works, ours incorporates texture in addition to shape information into a probabilistic constraint, and utilizes spatiotemporal regularization via a Maximum A Posteriori framework. We present comparative results to illustrate the improvement gain.

M3 - Conference Contribution (Conference Proceeding)

BT - MICCAI Workshop on Cardiovascular Intervetional Imaging and Biophysical Modelling

ER -

Appearance based Spatiotemporal Constraint for LV Segmentation in 4D Cardiac SPECT

Abstract

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