Validation of an automated cervical spinal cord segmentation in brain MRI

被引：0

作者：

Disselhorst, J. A. ^{[1
]}

Andelova, M. ^{[2
,3
]}

Krasensky, J. ^{[2
,4
]}

Kober, T. ^{[1
]}

Marechal, B. ^{[1
]}

Vaneckova, M. ^{[2
,4
]}

机构：

[1] Siemens Healthcare AG, Adv Clin Imaging Technol, Lausanne, Switzerland

[2] Charles Univ Prague, Prague, Czech Republic

[3] Gen Univ Hosp, Dept Neurol, Fac Med 1, Prague, Czech Republic

[4] Gen Univ Hosp, Dept Radiol, Fac Med 1, Prague, Czech Republic

来源：

MULTIPLE SCLEROSIS JOURNAL | 2021年 / 27卷 / 2_SUPPL期

关键词：

D O I：

暂无

中图分类号：

R74 [神经病学与精神病学];

学科分类号：

摘要：

P525

引用

页码：473 / 474

页数：2

共 2 条

[1] Additive Effect of Spinal Cord Volume, Diffuse and Focal Cord Pathology on Disability in Multiple Sclerosis [J].

Andelova, Michaela ;

Uher, Tomas ;

Krasensky, Jan ;

Sobisek, Lukas ;

Kusova, Eliska ;

Srpova, Barbora ;

Vodehnalova, Karolina ;

Friedova, Lucie ;

Motyl, Jiri ;

Preiningerova, Jana Lizrova ;

Havrdova, Eva Kubala ;

Horakova, Dana ;

Vaneckova, Manuela .

FRONTIERS IN NEUROLOGY, 2019, 10

[2] nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation [J].

Isensee, Fabian ;

Jaeger, Paul F. ;

Kohl, Simon A. A. ;

Petersen, Jens ;

Maier-Hein, Klaus H. .

NATURE METHODS, 2021, 18 (02) :203-+

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