A Hybrid Deep Learning Framework for Integrated Segmentation and Registration: Evaluation on Longitudinal White Matter Tract Changes

Baoyue Li; Wiro Niessen; Stefan Klein; Marius de Groot; Arfan Ikram; Meike Vernooij; Esther Bron

doi:10.1007/978-3-030-32248-9_72

A Hybrid Deep Learning Framework for Integrated Segmentation and Registration: Evaluation on Longitudinal White Matter Tract Changes

Baoyue Li^*, Wiro Niessen, Stefan Klein, Marius de Groot, Arfan Ikram, Meike Vernooij, Esther Bron

^*Corresponding author for this work

Research output: Chapter/Conference proceeding › Chapter › Academic

28 Citations (Scopus)

Original language	Undefined/Unknown
Title of host publication	International Conference on Medical Image Computing and Computer-Assisted Intervention : Medical Image Computing and Computer Assisted Intervention – MICCAI 2019
Place of Publication	[S.l.]
Publisher	Springer Nature
Pages	645-653
ISBN (Print)	9783030322472
DOIs	https://doi.org/10.1007/978-3-030-32248-9_72
Publication status	Published - 2019

Publication series

Series	Lecture Notes in Computer Science
Volume	11766

Research programs

EMC NIHES-03-30-03

Access to Document

10.1007/978-3-030-32248-9_72

Cite this

Li, B., Niessen, W., Klein, S., de Groot, M., Ikram, A., Vernooij, M., & Bron, E. (2019). A Hybrid Deep Learning Framework for Integrated Segmentation and Registration: Evaluation on Longitudinal White Matter Tract Changes. In International Conference on Medical Image Computing and Computer-Assisted Intervention : Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 (pp. 645-653). Springer Nature. https://doi.org/10.1007/978-3-030-32248-9_72

Li, Baoyue ; Niessen, Wiro ; Klein, Stefan et al. / A Hybrid Deep Learning Framework for Integrated Segmentation and Registration : Evaluation on Longitudinal White Matter Tract Changes. International Conference on Medical Image Computing and Computer-Assisted Intervention : Medical Image Computing and Computer Assisted Intervention – MICCAI 2019. [S.l.] : Springer Nature, 2019. pp. 645-653 (Lecture Notes in Computer Science, Vol. 11766).

@inbook{245c8cf7d6bf41bbb75ec74b378cc3cd,

title = "A Hybrid Deep Learning Framework for Integrated Segmentation and Registration: Evaluation on Longitudinal White Matter Tract Changes",

author = "Baoyue Li and Wiro Niessen and Stefan Klein and {de Groot}, Marius and Arfan Ikram and Meike Vernooij and Esther Bron",

year = "2019",

doi = "10.1007/978-3-030-32248-9_72",

language = "Undefined/Unknown",

isbn = "9783030322472",

series = "Lecture Notes in Computer Science",

publisher = "Springer Nature",

pages = "645--653",

booktitle = "International Conference on Medical Image Computing and Computer-Assisted Intervention : Medical Image Computing and Computer Assisted Intervention – MICCAI 2019",

address = "Germany",

}

Li, B, Niessen, W , Klein, S, de Groot, M, Ikram, A , Vernooij, M & Bron, E 2019, A Hybrid Deep Learning Framework for Integrated Segmentation and Registration: Evaluation on Longitudinal White Matter Tract Changes. in International Conference on Medical Image Computing and Computer-Assisted Intervention : Medical Image Computing and Computer Assisted Intervention – MICCAI 2019. Springer Nature, [S.l.], Lecture Notes in Computer Science, vol. 11766, pp. 645-653. https://doi.org/10.1007/978-3-030-32248-9_72

A Hybrid Deep Learning Framework for Integrated Segmentation and Registration: Evaluation on Longitudinal White Matter Tract Changes. / Li, Baoyue; Niessen, Wiro ; Klein, Stefan et al.
International Conference on Medical Image Computing and Computer-Assisted Intervention : Medical Image Computing and Computer Assisted Intervention – MICCAI 2019. [S.l.]: Springer Nature, 2019. p. 645-653 (Lecture Notes in Computer Science, Vol. 11766).

Research output: Chapter/Conference proceeding › Chapter › Academic

TY - CHAP

T1 - A Hybrid Deep Learning Framework for Integrated Segmentation and Registration

T2 - Evaluation on Longitudinal White Matter Tract Changes

AU - Li, Baoyue

AU - Niessen, Wiro

AU - Klein, Stefan

AU - de Groot, Marius

AU - Ikram, Arfan

AU - Vernooij, Meike

AU - Bron, Esther

PY - 2019

Y1 - 2019

U2 - 10.1007/978-3-030-32248-9_72

DO - 10.1007/978-3-030-32248-9_72

M3 - Chapter

SN - 9783030322472

T3 - Lecture Notes in Computer Science

SP - 645

EP - 653

BT - International Conference on Medical Image Computing and Computer-Assisted Intervention : Medical Image Computing and Computer Assisted Intervention – MICCAI 2019

PB - Springer Nature

CY - [S.l.]

ER -

Li B, Niessen W , Klein S, de Groot M, Ikram A , Vernooij M et al. A Hybrid Deep Learning Framework for Integrated Segmentation and Registration: Evaluation on Longitudinal White Matter Tract Changes. In International Conference on Medical Image Computing and Computer-Assisted Intervention : Medical Image Computing and Computer Assisted Intervention – MICCAI 2019. [S.l.]: Springer Nature. 2019. p. 645-653. (Lecture Notes in Computer Science, Vol. 11766). Epub 2019 Oct 10. doi: 10.1007/978-3-030-32248-9_72