Sequence-Type Classification of Brain MRI for Acute Stroke Using a Self-Supervised Machine Learning Algorithm

We propose a self-supervised machine learning (ML) algorithm for sequence-type classification of brain MRI using a supervisory signal from DICOM metadata (i.e., a rule-based virtual label). A total of 1787 brain MRI datasets were constructed, including 1531 from hospitals and 256 from multi-center t...

وصف كامل

التفاصيل البيبلوغرافية
الحاوية / القاعدة:Diagnostics
المؤلفون الرئيسيون: Seongwon Na, Yousun Ko, Su Jung Ham, Yu Sub Sung, Mi-Hyun Kim, Youngbin Shin, Seung Chai Jung, Chung Ju, Byung Su Kim, Kyoungro Yoon, Kyung Won Kim
التنسيق: مقال
اللغة:الإنجليزية
منشور في: MDPI AG 2023-12-01
الموضوعات:
magnetic resonance image
machine learning
metadata
الوصول للمادة أونلاين:https://www.mdpi.com/2075-4418/14/1/70

الانترنت

https://www.mdpi.com/2075-4418/14/1/70

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