Automatic segmentation of fetal brain using diffusion-weighted imaging cues

Rosita Shishegar; Anand A. Joshi; Mary Tolcos; David W. Walker; Leigh A. Johnston

doi:10.1109/ISBI.2017.7950640

Automatic segmentation of fetal brain using diffusion-weighted imaging cues

Rosita Shishegar, Anand A. Joshi, Mary Tolcos, David W. Walker, Leigh A. Johnston

Hudson Institute - Department of Molecular and Translational Science

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

3 Citations (Scopus)

Abstract

Segmentation of the developing cortical plate from MRI data of the post-mortem fetal brain is highly challenging due to partial volume effects, low contrast, and heterogeneous maturation caused by ongoing myelination processes. We present a new atlas-free method that segments the inner and outer boundaries of the cortical plate in fetal brains by exploiting diffusion-weighted imaging cues and using a cortical thickness constraint. The accuracy of the segmentation algorithm is demonstrated by application to fetal sheep brain MRI data, and is shown to produce results comparable to manual segmentation and more accurate than semi-automatic segmentation.

Original language	English
Title of host publication	IEEE International Symposium on Biomedical Imaging
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	804-807
Number of pages	4
ISBN (Electronic)	9781509011711
DOIs	https://doi.org/10.1109/ISBI.2017.7950640
Publication status	Published - 19 Jun 2017
Event	IEEE International Symposium on Biomedical Imaging (ISBI) 2017 - Melbourne Convention and Exhibition Centre, Melbourne, Australia Duration: 18 Apr 2017 → 21 Apr 2017 Conference number: 14th http://biomedicalimaging.org/2017/ https://ieeexplore-ieee-org.ezproxy.lib.monash.edu.au/xpl/conhome/7944115/proceeding

Conference

Conference	IEEE International Symposium on Biomedical Imaging (ISBI) 2017
Abbreviated title	ISBI 2017
Country/Territory	Australia
City	Melbourne
Period	18/04/17 → 21/04/17
Other	ISBI is a joint initiative from the IEEE Signal Processing Society (SPS) and the IEEE Engineering in Medicine and Biology Society (EMBS). The 2017 meeting will include tutorials, and a scientific program composed of plenary talks, invited special sessions, challenges, as well as oral and poster presentations of peer-reviewed papers.
Internet address	http://biomedicalimaging.org/2017/ https://ieeexplore-ieee-org.ezproxy.lib.monash.edu.au/xpl/conhome/7944115/proceeding

Keywords

segmentation
atlas-free
fetal brain
diffusion-weighted imaging
tractography

Access to Document

10.1109/ISBI.2017.7950640

Cite this

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title = "Automatic segmentation of fetal brain using diffusion-weighted imaging cues",

abstract = "Segmentation of the developing cortical plate from MRI data of the post-mortem fetal brain is highly challenging due to partial volume effects, low contrast, and heterogeneous maturation caused by ongoing myelination processes. We present a new atlas-free method that segments the inner and outer boundaries of the cortical plate in fetal brains by exploiting diffusion-weighted imaging cues and using a cortical thickness constraint. The accuracy of the segmentation algorithm is demonstrated by application to fetal sheep brain MRI data, and is shown to produce results comparable to manual segmentation and more accurate than semi-automatic segmentation.",

keywords = "segmentation, atlas-free, fetal brain, diffusion-weighted imaging, tractography",

author = "Rosita Shishegar and Joshi, {Anand A.} and Mary Tolcos and Walker, {David W.} and Johnston, {Leigh A.}",

year = "2017",

month = jun,

day = "19",

doi = "10.1109/ISBI.2017.7950640",

language = "English",

pages = "804--807",

booktitle = "IEEE International Symposium on Biomedical Imaging",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States of America",

note = "IEEE International Symposium on Biomedical Imaging (ISBI) 2017, ISBI 2017 ; Conference date: 18-04-2017 Through 21-04-2017",

url = "http://biomedicalimaging.org/2017/, https://ieeexplore-ieee-org.ezproxy.lib.monash.edu.au/xpl/conhome/7944115/proceeding",

}

Shishegar, R, Joshi, AA, Tolcos, M, Walker, DW & Johnston, LA 2017, Automatic segmentation of fetal brain using diffusion-weighted imaging cues. in IEEE International Symposium on Biomedical Imaging. IEEE, Institute of Electrical and Electronics Engineers, pp. 804-807, IEEE International Symposium on Biomedical Imaging (ISBI) 2017, Melbourne, Victoria, Australia, 18/04/17. https://doi.org/10.1109/ISBI.2017.7950640

Automatic segmentation of fetal brain using diffusion-weighted imaging cues. / Shishegar, Rosita; Joshi, Anand A.; Tolcos, Mary et al.
IEEE International Symposium on Biomedical Imaging. IEEE, Institute of Electrical and Electronics Engineers, 2017. p. 804-807.

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

TY - GEN

T1 - Automatic segmentation of fetal brain using diffusion-weighted imaging cues

AU - Shishegar, Rosita

AU - Joshi, Anand A.

AU - Tolcos, Mary

AU - Walker, David W.

AU - Johnston, Leigh A.

N1 - Conference code: 14th

PY - 2017/6/19

Y1 - 2017/6/19

N2 - Segmentation of the developing cortical plate from MRI data of the post-mortem fetal brain is highly challenging due to partial volume effects, low contrast, and heterogeneous maturation caused by ongoing myelination processes. We present a new atlas-free method that segments the inner and outer boundaries of the cortical plate in fetal brains by exploiting diffusion-weighted imaging cues and using a cortical thickness constraint. The accuracy of the segmentation algorithm is demonstrated by application to fetal sheep brain MRI data, and is shown to produce results comparable to manual segmentation and more accurate than semi-automatic segmentation.

AB - Segmentation of the developing cortical plate from MRI data of the post-mortem fetal brain is highly challenging due to partial volume effects, low contrast, and heterogeneous maturation caused by ongoing myelination processes. We present a new atlas-free method that segments the inner and outer boundaries of the cortical plate in fetal brains by exploiting diffusion-weighted imaging cues and using a cortical thickness constraint. The accuracy of the segmentation algorithm is demonstrated by application to fetal sheep brain MRI data, and is shown to produce results comparable to manual segmentation and more accurate than semi-automatic segmentation.

KW - segmentation

KW - atlas-free

KW - fetal brain

KW - diffusion-weighted imaging

KW - tractography

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M3 - Conference Paper

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PB - IEEE, Institute of Electrical and Electronics Engineers

T2 - IEEE International Symposium on Biomedical Imaging (ISBI) 2017

Y2 - 18 April 2017 through 21 April 2017

ER -

Automatic segmentation of fetal brain using diffusion-weighted imaging cues

Abstract

Conference

Keywords

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