An open presurgery MRI dataset of people with epilepsy and focal cortical dysplasia type II

被引:12
作者
Schuch, Fabiane [1 ]
Walger, Lennart [1 ]
Schmitz, Matthias [1 ]
David, Bastian [1 ]
Bauer, Tobias [1 ]
Harms, Antonia [1 ]
Fischbach, Laura [1 ]
Schulte, Freya [1 ]
Schidlowski, Martin [1 ]
Reiter, Johannes [1 ]
Bitzer, Felix [1 ]
von Wrede, Randi [1 ]
Racz, Atilla [1 ]
Baumgartner, Tobias [1 ]
Borger, Valeri [2 ]
Schneider, Matthias [2 ]
Flender, Achim [3 ]
Becker, Albert [4 ]
Vatter, Hartmut [2 ]
Weber, Bernd [5 ]
Specht-Riemenschneider, Louisa [6 ]
Radbruch, Alexander [7 ]
Surges, Rainer [1 ]
Rueber, Theodor [1 ]
机构
[1] Univ Hosp Bonn, Dept Epileptol, Bonn, Germany
[2] Univ Hosp Bonn, Dept Neurosurg, Bonn, Germany
[3] Univ Hosp Bonn, Med Fac, Bonn, Germany
[4] Univ Hosp Bonn, Dept Neuropathol, Sect Translat Epilepsy Res, Bonn, Germany
[5] Univ Hosp Bonn, Inst Expt Epileptol & Cognit Res, Bonn, Germany
[6] Univ Bonn, Fac Law, Chair Civil Law Informat Law & Data Law, Bonn, Germany
[7] Univ Hosp Bonn, Dept Neuroradiol, Bonn, Germany
关键词
HOC TASK-FORCE; AUTOMATED DETECTION; IMPROVES DETECTION; CLASSIFICATION;
D O I
10.1038/s41597-023-02386-7
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Automated detection of lesions using artificial intelligence creates new standards in medical imaging. For people with epilepsy, automated detection of focal cortical dysplasias (FCDs) is widely used because subtle FCDs often escape conventional neuroradiological diagnosis. Accurate recognition of FCDs, however, is of outstanding importance for affected people, as surgical resection of the dysplastic cortex is associated with a high chance of postsurgical seizure freedom. Here, we make publicly available a dataset of 85 people affected by epilepsy due to FCD type II and 85 healthy control persons. We publish 3D-T1 and 3D-FLAIR, manually labeled regions of interest, and carefully selected clinical features. The open presurgery MRI dataset may be used to validate existing automated algorithms of FCD detection as well as to create new approaches. Most importantly, it will enable comparability of already existing approaches and support a more widespread use of automated lesion detection tools.
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收藏
页数:7
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