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Research ArticlePediatric Neuroimaging

Application of Automatic Segmentation on Super-Resolution Reconstruction MR Images of the Abnormal Fetal Brain

T. Deprest, L. Fidon, F. De Keyzer, M. Ebner, J. Deprest, P. Demaerel, L. De Catte, T. Vercauteren, S. Ourselin, S. Dymarkowski and M. Aertsen
American Journal of Neuroradiology March 2023, DOI: https://doi.org/10.3174/ajnr.A7808
T. Deprest
aFrom the Departments of Radiology (T.D., F.D.K., P.D., S.D., M.A.)
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L. Fidon
cSchool of Biomedical Engineering and Imaging Sciences (L.F., M.E., T.V., S.O.), King’s College London, London, UK
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F. De Keyzer
aFrom the Departments of Radiology (T.D., F.D.K., P.D., S.D., M.A.)
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M. Ebner
cSchool of Biomedical Engineering and Imaging Sciences (L.F., M.E., T.V., S.O.), King’s College London, London, UK
eDepartment of Medical Physics and Biomedical Engineering (M.E., T.V.), University College London, London, UK
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J. Deprest
bGynaecology and Obstetrics (J.D., L.D.C., T.V.), University Hospitals Leuven, Belgium
dInstitute for Women's Health (J.D.)
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P. Demaerel
aFrom the Departments of Radiology (T.D., F.D.K., P.D., S.D., M.A.)
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L. De Catte
bGynaecology and Obstetrics (J.D., L.D.C., T.V.), University Hospitals Leuven, Belgium
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T. Vercauteren
bGynaecology and Obstetrics (J.D., L.D.C., T.V.), University Hospitals Leuven, Belgium
cSchool of Biomedical Engineering and Imaging Sciences (L.F., M.E., T.V., S.O.), King’s College London, London, UK
eDepartment of Medical Physics and Biomedical Engineering (M.E., T.V.), University College London, London, UK
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S. Ourselin
cSchool of Biomedical Engineering and Imaging Sciences (L.F., M.E., T.V., S.O.), King’s College London, London, UK
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S. Dymarkowski
aFrom the Departments of Radiology (T.D., F.D.K., P.D., S.D., M.A.)
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M. Aertsen
aFrom the Departments of Radiology (T.D., F.D.K., P.D., S.D., M.A.)
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References

  1. 1.↵
    1. Pugash D,
    2. Brugger PC,
    3. Bettelheim D, et al
    . Prenatal ultrasound and fetal MRI: the comparative value of each modality in prenatal diagnosis. Eur J Radiol 2008;68:214–26 doi:10.1016/j.ejrad.2008.06.031 pmid:18790583
    CrossRefPubMed
  2. 2.↵
    1. Ebner M,
    2. Wang G,
    3. Li W, et al
    . An automated framework for localization, segmentation and super-resolution reconstruction of fetal brain MRI. Neuroimage 2020;206:116324 doi:10.1016/j.neuroimage.2019.116324 pmid:31704293
    CrossRefPubMed
  3. 3.↵
    1. Jiang S,
    2. Xue H,
    3. Glover A, et al
    . MRI of moving subjects using multislice snapshot images with volume reconstruction (SVR): application to fetal, neonatal, and adult brain studies. IEEE Trans Med Imaging 2007;26:967–80 doi:10.1109/TMI.2007.895456 pmid:17649910
    CrossRefPubMedWeb of Science
  4. 4.↵
    1. Gholipour A,
    2. Estroff JA,
    3. Warfield SK
    . Robust super-resolution volume reconstruction from slice acquisitions: application to fetal brain MRI. IEEE Trans Med Imaging 2010;29:1739–58 doi:10.1109/TMI.2010.2051680 pmid:20529730
    CrossRefPubMedWeb of Science
  5. 5.↵
    1. Kuklisova-Murgasova M,
    2. Quaghebeur G,
    3. Rutherford MA, et al
    . Reconstruction of fetal brain MRI with intensity matching and complete outlier removal. Med Image Anal 2012;16:1550–64 doi:10.1016/j.media.2012.07.004 pmid:22939612
    CrossRefPubMed
  6. 6.↵
    1. Kainz B,
    2. Steinberger M,
    3. Wein W, et al
    . Fast volume reconstruction from motion corrupted stacks of 2D slices. IEEE Trans Med Imaging 2015;34:1901–13 doi:10.1109/TMI.2015.2415453 pmid:25807565
    CrossRefPubMed
  7. 7.↵
    1. Prayer D,
    2. Kasprian G,
    3. Krampl E, et al
    . MRI of normal fetal brain development. Eur J Radiol 2006;57:199–216 doi:10.1016/j.ejrad.2005.11.020 pmid:16413984
    CrossRefPubMedWeb of Science
  8. 8.↵
    1. Litjens G,
    2. Kooi T,
    3. Bejnordi BE, et al
    . A survey on deep learning in medical image analysis. Med Image Anal 2017;42:60–88 doi:10.1016/j.media.2017.07.005 pmid:28778026
    CrossRefPubMed
  9. 9.↵
    1. Akkus Z,
    2. Galimzianova A,
    3. Hoogi A, et al
    . Deep learning for brain MRI segmentation: state of the art and future directions. J Digit Imaging 2017;30:449–59 doi:10.1007/s10278-017-9983-4 pmid:28577131
    CrossRefPubMed
  10. 10.↵
    1. Makropoulos A,
    2. Counsell SJ,
    3. Rueckert D
    . A review on automatic fetal and neonatal brain MRI segmentation. Neuroimage 2018;170:231–48 doi:10.1016/j.neuroimage.2017.06.074 pmid:28666878
    CrossRefPubMed
  11. 11.↵
    1. Khalili N,
    2. Lessmann N,
    3. Turk E, et al
    . Automatic brain tissue segmentation in fetal MRI using convolutional neural networks. Magn Reson Imaging 2019;64:77–89 doi:10.1016/j.mri.2019.05.020 pmid:31181246
    CrossRefPubMed
  12. 12.↵
    1. Wang Q,
    2. Gomez A,
    3. Hutter J, et al
    . Smart Ultrasound Imaging and Perinatal, Preterm and Paediatric Image Analysis. Springer-Verlag International Publishing; 2019
  13. 13.↵
    1. Aertsen M,
    2. Diogo MC,
    3. Dymarkowski S, et al
    . MRI for dummies: what the fetal medicine specialist should know about acquisitions and sequences. Prenatal Diagnosis 2020;40:6–17 doi:10.1002/pd.5579 pmid:31618472
    CrossRefPubMed
  14. 14.↵
    1. Chouzenoux E,
    2. Gérard H,
    3. Pesquet JC
    . General risk measures for robust machine learning. arXiv [Internet] May 24, 2019. http://arxiv.org/abs/1904.11707. Accessed March 13, 2021
  15. 15.↵
    1. Duchi J,
    2. Glynn P,
    3. Namkoong H
    . Statistics of robust optimization: a generalized empirical likelihood approach. arXiv [Internet] October 11, 2016. http://arxiv.org/abs/1610.03425. Accessed April 13, 2021
  16. 16.↵
    1. Namkoong H,
    2. Duchi JC
    . Stochastic gradient methods for distributionally robust optimization with f-divergences. In: Proceedings of the Thirtieth Conference on Neural Information Processing Systems, Barcelona, Spain. December 5–10, 2016
  17. 17.↵
    1. Rafique H,
    2. Liu M,
    3. Lin Q, et al
    . Non-convex min-max optimization: provable algorithms and applications in machine learning. arXiv October 4, 2018. http://arxiv.org/abs/1810.02060. Accessed April 13, 2021
  18. 18.↵
    1. Fidon L,
    2. Ourselin S,
    3. Vercauteren T
    . Distributionally robust deep learning using hardness weighted sampling. arXiv July 14, 2022, http://arxiv.org/abs/2001.02658. Accessed November 5, 2020
  19. 19.↵
    1. Sudre CH,
    2. Licandro K,
    3. Baumgartner C
    1. Fidon L,
    2. Aertsen M,
    3. Mufti N, et al
    . Distributionally robust segmentation of abnormal fetal brain 3D MRI. In: Sudre CH, Licandro K, Baumgartner C, et al., eds. Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis. 2021;12959:263–73 doi:10.1007/978-3-030-87735-4_25
    CrossRef
  20. 20.↵
    1. Bystron I,
    2. Blakemore C,
    3. Rakic P
    . Development of the human cerebral cortex: Boulder Committee revisited. Nat Rev Neurosci 2008;9:110–22 doi:10.1038/nrn2252 pmid:18209730
    CrossRefPubMedWeb of Science
  21. 21.↵
    1. Yushkevich PA,
    2. Piven J,
    3. Hazlett HC, et al
    . User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. Neuroimage 2006;31:1116–28 doi:10.1016/j.neuroimage.2006.01.015 pmid:16545965
    CrossRefPubMedWeb of Science
  22. 22.↵
    1. Bakas S,
    2. Reyes M,
    3. Jakab A, et al
    . Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS Challenge. arXiv July 14, 2019. http://arxiv.org/abs/1811.02629. Accessed December 22, 2020
  23. 23.↵
    1. Zijdenbos AP,
    2. Dawant BM,
    3. Margolin RA, et al
    . Morphometric analysis of white matter lesions in MR images: method and validation. IEEE Trans Med Imaging 1994;13:716–24 doi:10.1109/42.363096 pmid:18218550
    CrossRefPubMedWeb of Science
  24. 24.↵
    1. Trigo L,
    2. Eixarch E,
    3. Bottura I, et al
    . Prevalence of supratentorial anomalies assessed by fetal magnetic resonance in fetuses with open spina bifida. Ultrasound Obstet Gynecol 2022;59:804–12 doi:10.1002/UOG.23761 pmid:34396624
    CrossRefPubMed
  25. 25.↵
    1. Fidon L,
    2. Viola E,
    3. Mufti N, et al
    . A spatio-temporal atlas of the developing fetal brain with spina bifida aperta. Open Research Europe 2021;1:123 doi:10.12688/openreseurope.13914.1
    CrossRef
  26. 26.
    1. Habas PA,
    2. Kim K,
    3. Rousseau F, et al
    . Atlas-based segmentation of developing tissues in the human brain with quantitative validation in young fetuses. Hum Brain Mapp 2010;31:1348–58 doi:10.1002/hbm.20935 pmid:20108226
    CrossRefPubMedWeb of Science
  27. 27.
    1. Serag A,
    2. Kyriakopoulou V,
    3. Rutherford MA, et al
    . Multi-channel 4D probabilistic atlas of the developing brain: application to fetuses and neonates. Ann Br Mach Vis Assoc 2012;2012:1–14
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Cite this article
T. Deprest, L. Fidon, F. De Keyzer, M. Ebner, J. Deprest, P. Demaerel, L. De Catte, T. Vercauteren, S. Ourselin, S. Dymarkowski, M. Aertsen
Application of Automatic Segmentation on Super-Resolution Reconstruction MR Images of the Abnormal Fetal Brain
American Journal of Neuroradiology Mar 2023, DOI: 10.3174/ajnr.A7808

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Application of Automatic Segmentation on Super-Resolution Reconstruction MR Images of the Abnormal Fetal Brain
T. Deprest, L. Fidon, F. De Keyzer, M. Ebner, J. Deprest, P. Demaerel, L. De Catte, T. Vercauteren, S. Ourselin, S. Dymarkowski, M. Aertsen
American Journal of Neuroradiology Mar 2023, DOI: 10.3174/ajnr.A7808
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