Longitudinal Analysis of Pre-term Neonatal Brain Ventricle in Ultrasound Images Based on Convex Optimization

Wu Qiu; Jing Yuan; Jessica Kishimoto; Yimin Chen; Martin Rajchl; Eranga Ukwatta; Sandrine de Ribaupierre; Aaron Fenster

doi:10.1007/978-3-319-24574-4_57

Longitudinal Analysis of Pre-term Neonatal Brain Ventricle in Ultrasound Images Based on Convex Optimization

Wu Qiu, Jing Yuan, Jessica Kishimoto, Yimin Chen, Martin Rajchl, Eranga Ukwatta, Sandrine de Ribaupierre, Aaron Fenster

Department of Electrical Engineering

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

2 Citations (Scopus)

Abstract

Intraventricular hemorrhage (IVH) is a major cause of brain injury in preterm neonates and leads to dilatation of the ventricles. Measuring ventricular volume quantitatively is an important step in monitoring patients and evaluating treatment options. 3D ultrasound (US) has been developed to monitor ventricle volume as a biomarker for ventricular dilatation and deformation. Ventricle volume as a global indicator, however, does not allow for the precise analysis of local ventricular changes. In this work, we propose a 3D+t spatial-temporal nonlinear registration approach, which is used to analyze the detailed local changes of the ventricles of preterm IVH neonates from 3D US images. In particular, a novel sequential convex/dual optimization is introduced to extract the optimal 3D+t spatial-temporal deformable registration. The experiments with five patients with 4 time-point images for each patient showed that the proposed registration approach accurately and efficiently recovered the longitudinal deformation of the ventricles from 3D US images. To the best of our knowledge, this paper reports the first study on the longitudinal analysis of the ventriclar system of pre-term newborn brains from 3D US images.

Original language	English
Title of host publication	Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015
Subtitle of host publication	Proceedings, Part III
Editors	Nassir Navab, Joachim Hornegger, William M. Wells, Alejandro F. Frangi
Publisher	Springer, Cham
Pages	476-483
ISBN (Electronic)	9783319245744
ISBN (Print)	9783319245737
DOIs	https://doi.org/10.1007/978-3-319-24574-4_57
Publication status	Published - 2015
Event	18th International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI 2015) - Munich, Germany Duration: 5 Oct 2015 → 9 Oct 2015 https://www.miccai2015.org/frontend/index.php?sub=22

Publication series

Name	Lecture Notes in Computer Science
Volume	LNCS 9351
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	18th International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI 2015)
Abbreviated title	MICCAI 2015
Country/Territory	Germany
City	Munich
Period	5/10/15 → 9/10/15
Internet address	https://www.miccai2015.org/frontend/index.php?sub=22

Research Keywords

3D ultrasound
pre-term neonatal ventricles
spatial-temporal registration
convex optimization
DUAL OPTIMIZATION
MR-IMAGES
SEGMENTATION
DILATATION
SYSTEM
TRUS

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Qiu, W., Yuan, J., Kishimoto, J., Chen, Y., Rajchl, M., Ukwatta, E., de Ribaupierre, S., & Fenster, A. (2015). Longitudinal Analysis of Pre-term Neonatal Brain Ventricle in Ultrasound Images Based on Convex Optimization. In N. Navab, J. Hornegger, W. M. Wells, & A. F. Frangi (Eds.), Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015: Proceedings, Part III (pp. 476-483). (Lecture Notes in Computer Science; Vol. LNCS 9351). Springer, Cham. https://doi.org/10.1007/978-3-319-24574-4_57

Qiu, Wu ; Yuan, Jing ; Kishimoto, Jessica et al. / Longitudinal Analysis of Pre-term Neonatal Brain Ventricle in Ultrasound Images Based on Convex Optimization. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015: Proceedings, Part III. editor / Nassir Navab ; Joachim Hornegger ; William M. Wells ; Alejandro F. Frangi. Springer, Cham, 2015. pp. 476-483 (Lecture Notes in Computer Science).

@inproceedings{2e190a1318ba4fad9660cda21f39515f,

title = "Longitudinal Analysis of Pre-term Neonatal Brain Ventricle in Ultrasound Images Based on Convex Optimization",

abstract = "Intraventricular hemorrhage (IVH) is a major cause of brain injury in preterm neonates and leads to dilatation of the ventricles. Measuring ventricular volume quantitatively is an important step in monitoring patients and evaluating treatment options. 3D ultrasound (US) has been developed to monitor ventricle volume as a biomarker for ventricular dilatation and deformation. Ventricle volume as a global indicator, however, does not allow for the precise analysis of local ventricular changes. In this work, we propose a 3D+t spatial-temporal nonlinear registration approach, which is used to analyze the detailed local changes of the ventricles of preterm IVH neonates from 3D US images. In particular, a novel sequential convex/dual optimization is introduced to extract the optimal 3D+t spatial-temporal deformable registration. The experiments with five patients with 4 time-point images for each patient showed that the proposed registration approach accurately and efficiently recovered the longitudinal deformation of the ventricles from 3D US images. To the best of our knowledge, this paper reports the first study on the longitudinal analysis of the ventriclar system of pre-term newborn brains from 3D US images.",

keywords = "3D ultrasound, pre-term neonatal ventricles, spatial-temporal registration, convex optimization, DUAL OPTIMIZATION, MR-IMAGES, SEGMENTATION, DILATATION, SYSTEM, TRUS",

author = "Wu Qiu and Jing Yuan and Jessica Kishimoto and Yimin Chen and Martin Rajchl and Eranga Ukwatta and {de Ribaupierre}, Sandrine and Aaron Fenster",

year = "2015",

doi = "10.1007/978-3-319-24574-4_57",

language = "English",

isbn = "9783319245737",

series = "Lecture Notes in Computer Science",

publisher = "Springer, Cham",

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editor = "Nassir Navab and Joachim Hornegger and Wells, {William M.} and Frangi, {Alejandro F.}",

booktitle = "Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015",

note = "18th International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI 2015), MICCAI 2015 ; Conference date: 05-10-2015 Through 09-10-2015",

url = "https://www.miccai2015.org/frontend/index.php?sub=22",

}

Qiu, W, Yuan, J, Kishimoto, J, Chen, Y, Rajchl, M, Ukwatta, E, de Ribaupierre, S & Fenster, A 2015, Longitudinal Analysis of Pre-term Neonatal Brain Ventricle in Ultrasound Images Based on Convex Optimization. in N Navab, J Hornegger, WM Wells & AF Frangi (eds), Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015: Proceedings, Part III. Lecture Notes in Computer Science, vol. LNCS 9351, Springer, Cham, pp. 476-483, 18th International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI 2015), Munich, Germany, 5/10/15. https://doi.org/10.1007/978-3-319-24574-4_57

Longitudinal Analysis of Pre-term Neonatal Brain Ventricle in Ultrasound Images Based on Convex Optimization. / Qiu, Wu; Yuan, Jing; Kishimoto, Jessica et al.
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015: Proceedings, Part III. ed. / Nassir Navab; Joachim Hornegger; William M. Wells; Alejandro F. Frangi. Springer, Cham, 2015. p. 476-483 (Lecture Notes in Computer Science; Vol. LNCS 9351).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Longitudinal Analysis of Pre-term Neonatal Brain Ventricle in Ultrasound Images Based on Convex Optimization

AU - Qiu, Wu

AU - Yuan, Jing

AU - Kishimoto, Jessica

AU - Chen, Yimin

AU - Rajchl, Martin

AU - Ukwatta, Eranga

AU - de Ribaupierre, Sandrine

AU - Fenster, Aaron

PY - 2015

Y1 - 2015

N2 - Intraventricular hemorrhage (IVH) is a major cause of brain injury in preterm neonates and leads to dilatation of the ventricles. Measuring ventricular volume quantitatively is an important step in monitoring patients and evaluating treatment options. 3D ultrasound (US) has been developed to monitor ventricle volume as a biomarker for ventricular dilatation and deformation. Ventricle volume as a global indicator, however, does not allow for the precise analysis of local ventricular changes. In this work, we propose a 3D+t spatial-temporal nonlinear registration approach, which is used to analyze the detailed local changes of the ventricles of preterm IVH neonates from 3D US images. In particular, a novel sequential convex/dual optimization is introduced to extract the optimal 3D+t spatial-temporal deformable registration. The experiments with five patients with 4 time-point images for each patient showed that the proposed registration approach accurately and efficiently recovered the longitudinal deformation of the ventricles from 3D US images. To the best of our knowledge, this paper reports the first study on the longitudinal analysis of the ventriclar system of pre-term newborn brains from 3D US images.

AB - Intraventricular hemorrhage (IVH) is a major cause of brain injury in preterm neonates and leads to dilatation of the ventricles. Measuring ventricular volume quantitatively is an important step in monitoring patients and evaluating treatment options. 3D ultrasound (US) has been developed to monitor ventricle volume as a biomarker for ventricular dilatation and deformation. Ventricle volume as a global indicator, however, does not allow for the precise analysis of local ventricular changes. In this work, we propose a 3D+t spatial-temporal nonlinear registration approach, which is used to analyze the detailed local changes of the ventricles of preterm IVH neonates from 3D US images. In particular, a novel sequential convex/dual optimization is introduced to extract the optimal 3D+t spatial-temporal deformable registration. The experiments with five patients with 4 time-point images for each patient showed that the proposed registration approach accurately and efficiently recovered the longitudinal deformation of the ventricles from 3D US images. To the best of our knowledge, this paper reports the first study on the longitudinal analysis of the ventriclar system of pre-term newborn brains from 3D US images.

KW - 3D ultrasound

KW - pre-term neonatal ventricles

KW - spatial-temporal registration

KW - convex optimization

KW - DUAL OPTIMIZATION

KW - MR-IMAGES

KW - SEGMENTATION

KW - DILATATION

KW - SYSTEM

KW - TRUS

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UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84951861145&origin=recordpage

U2 - 10.1007/978-3-319-24574-4_57

DO - 10.1007/978-3-319-24574-4_57

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9783319245737

T3 - Lecture Notes in Computer Science

SP - 476

EP - 483

BT - Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015

A2 - Navab, Nassir

A2 - Hornegger, Joachim

A2 - Wells, William M.

A2 - Frangi, Alejandro F.

PB - Springer, Cham

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ER -

Qiu W, Yuan J, Kishimoto J, Chen Y, Rajchl M, Ukwatta E et al. Longitudinal Analysis of Pre-term Neonatal Brain Ventricle in Ultrasound Images Based on Convex Optimization. In Navab N, Hornegger J, Wells WM, Frangi AF, editors, Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015: Proceedings, Part III. Springer, Cham. 2015. p. 476-483. (Lecture Notes in Computer Science). Epub 2015 Nov 18. doi: 10.1007/978-3-319-24574-4_57

Longitudinal Analysis of Pre-term Neonatal Brain Ventricle in Ultrasound Images Based on Convex Optimization

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