Shape deformation descriptor using Fourier analysis

Adhi Harmoko Saputro; M. Marzuki Mustafa; Aini Hussain; Oteh Maskon; Ika Faizura Mohd Nor

doi:10.1109/IJCNN.2012.6252589

Shape deformation descriptor using Fourier analysis

Adhi Harmoko Saputro, M. Marzuki Mustafa, Aini Hussain, Oteh Maskon, Ika Faizura Mohd Nor

Department of Physics

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

Abstract

Deformation analysis of left ventricle (LV) shape could provide a new quantitative understanding of its abnormality. Currently, there is established motion estimation that allows accurate tracking of every point on the 2D echocardiography (2DE). This method produces a precise movement vector of each point in 2DE sequence. Analyzing this data using Fourier analysis could produce a new pattern to determine normal and abnormal deformation of LV. Observation of this method was performed on dataset acquired from 10 normal subjects and 10 patients. Two standard views (apical 2 and 4 chamber) were analyzed using a proposed technique to determine a novel insight of deformation. The results obtained are very promising and could be used as reference for future cardiac abnormality detection.

Original language	English
Title of host publication	2012 International Joint Conference on Neural Networks, IJCNN 2012
DOIs	https://doi.org/10.1109/IJCNN.2012.6252589
Publication status	Published - 2012
Event	2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Part of the 2012 IEEE World Congress on Computational Intelligence, WCCI 2012 - Brisbane, QLD, Australia Duration: 10 Jun 2012 → 15 Jun 2012

Publication series

Name	Proceedings of the International Joint Conference on Neural Networks

Conference

Conference	2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Part of the 2012 IEEE World Congress on Computational Intelligence, WCCI 2012
Country/Territory	Australia
City	Brisbane, QLD
Period	10/06/12 → 15/06/12

Keywords

fourier descriptor
left ventricle shape
non-rigid tracking
shape deformation

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10.1109/IJCNN.2012.6252589

Cite this

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title = "Shape deformation descriptor using Fourier analysis",

abstract = "Deformation analysis of left ventricle (LV) shape could provide a new quantitative understanding of its abnormality. Currently, there is established motion estimation that allows accurate tracking of every point on the 2D echocardiography (2DE). This method produces a precise movement vector of each point in 2DE sequence. Analyzing this data using Fourier analysis could produce a new pattern to determine normal and abnormal deformation of LV. Observation of this method was performed on dataset acquired from 10 normal subjects and 10 patients. Two standard views (apical 2 and 4 chamber) were analyzed using a proposed technique to determine a novel insight of deformation. The results obtained are very promising and could be used as reference for future cardiac abnormality detection.",

keywords = "fourier descriptor, left ventricle shape, non-rigid tracking, shape deformation",

author = "Saputro, {Adhi Harmoko} and Mustafa, {M. Marzuki} and Aini Hussain and Oteh Maskon and {Mohd Nor}, {Ika Faizura}",

year = "2012",

doi = "10.1109/IJCNN.2012.6252589",

language = "English",

isbn = "9781467314909",

series = "Proceedings of the International Joint Conference on Neural Networks",

booktitle = "2012 International Joint Conference on Neural Networks, IJCNN 2012",

note = "2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Part of the 2012 IEEE World Congress on Computational Intelligence, WCCI 2012 ; Conference date: 10-06-2012 Through 15-06-2012",

}

Saputro, AH, Mustafa, MM, Hussain, A, Maskon, O & Mohd Nor, IF 2012, Shape deformation descriptor using Fourier analysis. in 2012 International Joint Conference on Neural Networks, IJCNN 2012., 6252589, Proceedings of the International Joint Conference on Neural Networks, 2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Part of the 2012 IEEE World Congress on Computational Intelligence, WCCI 2012, Brisbane, QLD, Australia, 10/06/12. https://doi.org/10.1109/IJCNN.2012.6252589

Shape deformation descriptor using Fourier analysis. / Saputro, Adhi Harmoko; Mustafa, M. Marzuki; Hussain, Aini et al.
2012 International Joint Conference on Neural Networks, IJCNN 2012. 2012. 6252589 (Proceedings of the International Joint Conference on Neural Networks).

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

TY - GEN

T1 - Shape deformation descriptor using Fourier analysis

AU - Saputro, Adhi Harmoko

AU - Mustafa, M. Marzuki

AU - Hussain, Aini

AU - Maskon, Oteh

AU - Mohd Nor, Ika Faizura

PY - 2012

Y1 - 2012

N2 - Deformation analysis of left ventricle (LV) shape could provide a new quantitative understanding of its abnormality. Currently, there is established motion estimation that allows accurate tracking of every point on the 2D echocardiography (2DE). This method produces a precise movement vector of each point in 2DE sequence. Analyzing this data using Fourier analysis could produce a new pattern to determine normal and abnormal deformation of LV. Observation of this method was performed on dataset acquired from 10 normal subjects and 10 patients. Two standard views (apical 2 and 4 chamber) were analyzed using a proposed technique to determine a novel insight of deformation. The results obtained are very promising and could be used as reference for future cardiac abnormality detection.

AB - Deformation analysis of left ventricle (LV) shape could provide a new quantitative understanding of its abnormality. Currently, there is established motion estimation that allows accurate tracking of every point on the 2D echocardiography (2DE). This method produces a precise movement vector of each point in 2DE sequence. Analyzing this data using Fourier analysis could produce a new pattern to determine normal and abnormal deformation of LV. Observation of this method was performed on dataset acquired from 10 normal subjects and 10 patients. Two standard views (apical 2 and 4 chamber) were analyzed using a proposed technique to determine a novel insight of deformation. The results obtained are very promising and could be used as reference for future cardiac abnormality detection.

KW - fourier descriptor

KW - left ventricle shape

KW - non-rigid tracking

KW - shape deformation

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DO - 10.1109/IJCNN.2012.6252589

M3 - Conference contribution

AN - SCOPUS:84865081062

SN - 9781467314909

T3 - Proceedings of the International Joint Conference on Neural Networks

BT - 2012 International Joint Conference on Neural Networks, IJCNN 2012

T2 - 2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Part of the 2012 IEEE World Congress on Computational Intelligence, WCCI 2012

Y2 - 10 June 2012 through 15 June 2012

ER -

Shape deformation descriptor using Fourier analysis

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Keywords

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