Automated 3D Fetal Brain Segmentation Using an Optimized Deep Learning Approach

L. Zhao; J.D. Asis-Cruz; X. Feng; Y. Wu; K. Kapse; A. Largent; J. Quistorff; C. Lopez; D. Wu; K. Qing; C. Meyer; C. Limperopoulos

doi:10.3174/ajnr.A7419

Research ArticlePediatric Neuroimaging

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Automated 3D Fetal Brain Segmentation Using an Optimized Deep Learning Approach

L. Zhao, J.D. Asis-Cruz, X. Feng, Y. Wu, K. Kapse, A. Largent, J. Quistorff, C. Lopez, D. Wu, K. Qing, C. Meyer and C. Limperopoulos

American Journal of Neuroradiology March 2022, 43 (3) 448-454; DOI: https://doi.org/10.3174/ajnr.A7419

L. Zhao

aFrom the Department of Diagnostic Imaging and Radiology (L.Z., J.D.A.-C., Y.W., K.K., A.L., J.Q., C. Lopez, C. Limperopoulos), Developing Brain Institute, Children’s National, Washington, DC

bDepartment of Biomedical Engineering (L.Z., D.W.), Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, China

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J.D. Asis-Cruz

aFrom the Department of Diagnostic Imaging and Radiology (L.Z., J.D.A.-C., Y.W., K.K., A.L., J.Q., C. Lopez, C. Limperopoulos), Developing Brain Institute, Children’s National, Washington, DC

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X. Feng

cDepartment of Biomedical Engineering (X.F., C.M.), University of Virginia, Charlottesville, Virginia

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Y. Wu

aFrom the Department of Diagnostic Imaging and Radiology (L.Z., J.D.A.-C., Y.W., K.K., A.L., J.Q., C. Lopez, C. Limperopoulos), Developing Brain Institute, Children’s National, Washington, DC

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K. Kapse

aFrom the Department of Diagnostic Imaging and Radiology (L.Z., J.D.A.-C., Y.W., K.K., A.L., J.Q., C. Lopez, C. Limperopoulos), Developing Brain Institute, Children’s National, Washington, DC

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A. Largent

aFrom the Department of Diagnostic Imaging and Radiology (L.Z., J.D.A.-C., Y.W., K.K., A.L., J.Q., C. Lopez, C. Limperopoulos), Developing Brain Institute, Children’s National, Washington, DC

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J. Quistorff

aFrom the Department of Diagnostic Imaging and Radiology (L.Z., J.D.A.-C., Y.W., K.K., A.L., J.Q., C. Lopez, C. Limperopoulos), Developing Brain Institute, Children’s National, Washington, DC

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C. Lopez

aFrom the Department of Diagnostic Imaging and Radiology (L.Z., J.D.A.-C., Y.W., K.K., A.L., J.Q., C. Lopez, C. Limperopoulos), Developing Brain Institute, Children’s National, Washington, DC

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D. Wu

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K. Qing

dDepartment of Radiation Oncology (K.Q.), City of Hope National Center, Duarte, California

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C. Meyer

cDepartment of Biomedical Engineering (X.F., C.M.), University of Virginia, Charlottesville, Virginia

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C. Limperopoulos

aFrom the Department of Diagnostic Imaging and Radiology (L.Z., J.D.A.-C., Y.W., K.K., A.L., J.Q., C. Lopez, C. Limperopoulos), Developing Brain Institute, Children’s National, Washington, DC

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L. Zhao, J.D. Asis-Cruz, X. Feng, Y. Wu, K. Kapse, A. Largent, J. Quistorff, C. Lopez, D. Wu, K. Qing, C. Meyer, C. Limperopoulos

Automated 3D Fetal Brain Segmentation Using an Optimized Deep Learning Approach

American Journal of Neuroradiology Mar 2022, 43 (3) 448-454; DOI: 10.3174/ajnr.A7419

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Automated 3D Fetal Brain Segmentation Using an Optimized Deep Learning Approach

L. Zhao, J.D. Asis-Cruz, X. Feng, Y. Wu, K. Kapse, A. Largent, J. Quistorff, C. Lopez, D. Wu, K. Qing, C. Meyer, C. Limperopoulos

American Journal of Neuroradiology Mar 2022, 43 (3) 448-454; DOI: 10.3174/ajnr.A7419

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