Towards Whole Placenta Segmentation at Late Gestation Using Multi-view Ultrasound Images

Veronika A. Zimmer; Alberto Gomez; Emily Skelton; Nicolas Toussaint; Tong Zhang; Bishesh Khanal; Robert Wright; Yohan Noh; Alison Ho; Jacqueline Matthew; Joseph V. Hajnal; Julia A. Schnabel

doi:10.1007/978-3-030-32254-0_70

Towards Whole Placenta Segmentation at Late Gestation Using Multi-view Ultrasound Images

Veronika A. Zimmer, Alberto Gomez, Emily Skelton, Nicolas Toussaint, Tong Zhang, Bishesh Khanal, Robert Wright, Yohan Noh, Alison Ho, Jacqueline Matthew, Joseph V. Hajnal, Julia A. Schnabel

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

14 Scopus citations

Abstract

We propose a method to extract the human placenta at late gestation using multi-view 3D US images. This is the first step towards automatic quantification of placental volume and morphology from US images along the whole pregnancy beyond early stages (where the entire placenta can be captured with a single 3D US image). Our method uses 3D US images from different views acquired with a multi-probe system. A whole placenta segmentation is obtained from these images by using a novel technique based on 3D convolutional neural networks. We demonstrate the performance of our method on 3D US images of the placenta in the last trimester. We achieve a high Dice overlap of up to 0.8 with respect to manual annotations, and the derived placental volumes are comparable to corresponding volumes extracted from MR.

Original language	English
Title of host publication	Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 - 22nd International Conference, Proceedings
Editors	Dinggang Shen, Pew-Thian Yap, Tianming Liu, Terry M. Peters, Ali Khan, Lawrence H. Staib, Caroline Essert, Sean Zhou
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	628-636
Number of pages	9
ISBN (Print)	9783030322533
DOIs	https://doi.org/10.1007/978-3-030-32254-0_70
State	Published - 2019
Externally published	Yes
Event	22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019 - Shenzhen, China Duration: 13 Oct 2019 → 17 Oct 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11768 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019
Country/Territory	China
City	Shenzhen
Period	13/10/19 → 17/10/19

Access to Document

10.1007/978-3-030-32254-0_70

Cite this

Zimmer, V. A., Gomez, A., Skelton, E., Toussaint, N., Zhang, T., Khanal, B., Wright, R., Noh, Y., Ho, A., Matthew, J., Hajnal, J. V., & Schnabel, J. A. (2019). Towards Whole Placenta Segmentation at Late Gestation Using Multi-view Ultrasound Images. In D. Shen, P.-T. Yap, T. Liu, T. M. Peters, A. Khan, L. H. Staib, C. Essert, & S. Zhou (Eds.), Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 - 22nd International Conference, Proceedings (pp. 628-636). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11768 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-32254-0_70

Zimmer, Veronika A. ; Gomez, Alberto ; Skelton, Emily et al. / Towards Whole Placenta Segmentation at Late Gestation Using Multi-view Ultrasound Images. Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 - 22nd International Conference, Proceedings. editor / Dinggang Shen ; Pew-Thian Yap ; Tianming Liu ; Terry M. Peters ; Ali Khan ; Lawrence H. Staib ; Caroline Essert ; Sean Zhou. Springer Science and Business Media Deutschland GmbH, 2019. pp. 628-636 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{88b33adb30894c58af6603a3c96e4b21,

title = "Towards Whole Placenta Segmentation at Late Gestation Using Multi-view Ultrasound Images",

abstract = "We propose a method to extract the human placenta at late gestation using multi-view 3D US images. This is the first step towards automatic quantification of placental volume and morphology from US images along the whole pregnancy beyond early stages (where the entire placenta can be captured with a single 3D US image). Our method uses 3D US images from different views acquired with a multi-probe system. A whole placenta segmentation is obtained from these images by using a novel technique based on 3D convolutional neural networks. We demonstrate the performance of our method on 3D US images of the placenta in the last trimester. We achieve a high Dice overlap of up to 0.8 with respect to manual annotations, and the derived placental volumes are comparable to corresponding volumes extracted from MR.",

author = "Zimmer, {Veronika A.} and Alberto Gomez and Emily Skelton and Nicolas Toussaint and Tong Zhang and Bishesh Khanal and Robert Wright and Yohan Noh and Alison Ho and Jacqueline Matthew and Hajnal, {Joseph V.} and Schnabel, {Julia A.}",

note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019 ; Conference date: 13-10-2019 Through 17-10-2019",

year = "2019",

doi = "10.1007/978-3-030-32254-0_70",

language = "English",

isbn = "9783030322533",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "628--636",

editor = "Dinggang Shen and Pew-Thian Yap and Tianming Liu and Peters, {Terry M.} and Ali Khan and Staib, {Lawrence H.} and Caroline Essert and Sean Zhou",

booktitle = "Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 - 22nd International Conference, Proceedings",

address = "Germany",

}

Zimmer, VA, Gomez, A, Skelton, E, Toussaint, N, Zhang, T, Khanal, B, Wright, R, Noh, Y, Ho, A, Matthew, J, Hajnal, JV & Schnabel, JA 2019, Towards Whole Placenta Segmentation at Late Gestation Using Multi-view Ultrasound Images. in D Shen, P-T Yap, T Liu, TM Peters, A Khan, LH Staib, C Essert & S Zhou (eds), Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 - 22nd International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11768 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 628-636, 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019, Shenzhen, China, 13/10/19. https://doi.org/10.1007/978-3-030-32254-0_70

Towards Whole Placenta Segmentation at Late Gestation Using Multi-view Ultrasound Images. / Zimmer, Veronika A.; Gomez, Alberto; Skelton, Emily et al.
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 - 22nd International Conference, Proceedings. ed. / Dinggang Shen; Pew-Thian Yap; Tianming Liu; Terry M. Peters; Ali Khan; Lawrence H. Staib; Caroline Essert; Sean Zhou. Springer Science and Business Media Deutschland GmbH, 2019. p. 628-636 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11768 LNCS).

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

TY - GEN

T1 - Towards Whole Placenta Segmentation at Late Gestation Using Multi-view Ultrasound Images

AU - Zimmer, Veronika A.

AU - Gomez, Alberto

AU - Skelton, Emily

AU - Toussaint, Nicolas

AU - Zhang, Tong

AU - Khanal, Bishesh

AU - Wright, Robert

AU - Noh, Yohan

AU - Ho, Alison

AU - Matthew, Jacqueline

AU - Hajnal, Joseph V.

AU - Schnabel, Julia A.

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N2 - We propose a method to extract the human placenta at late gestation using multi-view 3D US images. This is the first step towards automatic quantification of placental volume and morphology from US images along the whole pregnancy beyond early stages (where the entire placenta can be captured with a single 3D US image). Our method uses 3D US images from different views acquired with a multi-probe system. A whole placenta segmentation is obtained from these images by using a novel technique based on 3D convolutional neural networks. We demonstrate the performance of our method on 3D US images of the placenta in the last trimester. We achieve a high Dice overlap of up to 0.8 with respect to manual annotations, and the derived placental volumes are comparable to corresponding volumes extracted from MR.

AB - We propose a method to extract the human placenta at late gestation using multi-view 3D US images. This is the first step towards automatic quantification of placental volume and morphology from US images along the whole pregnancy beyond early stages (where the entire placenta can be captured with a single 3D US image). Our method uses 3D US images from different views acquired with a multi-probe system. A whole placenta segmentation is obtained from these images by using a novel technique based on 3D convolutional neural networks. We demonstrate the performance of our method on 3D US images of the placenta in the last trimester. We achieve a high Dice overlap of up to 0.8 with respect to manual annotations, and the derived placental volumes are comparable to corresponding volumes extracted from MR.

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SN - 9783030322533

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 - 22nd International Conference, Proceedings

A2 - Shen, Dinggang

A2 - Yap, Pew-Thian

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A2 - Khan, Ali

A2 - Staib, Lawrence H.

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PB - Springer Science and Business Media Deutschland GmbH

T2 - 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019

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Zimmer VA, Gomez A, Skelton E, Toussaint N, Zhang T, Khanal B et al. Towards Whole Placenta Segmentation at Late Gestation Using Multi-view Ultrasound Images. In Shen D, Yap PT, Liu T, Peters TM, Khan A, Staib LH, Essert C, Zhou S, editors, Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 - 22nd International Conference, Proceedings. Springer Science and Business Media Deutschland GmbH. 2019. p. 628-636. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-32254-0_70

Towards Whole Placenta Segmentation at Late Gestation Using Multi-view Ultrasound Images

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