Leveraging Attention-Based Convolutional Neural Networks for Meningioma Classification in Computational Histopathology

Leveraging Attention-Based Convolutional Neural Networks for Meningioma Classification in Computational Histopathology

Convolutional neural networks (CNNs) are becoming increasingly valuable tools for advanced computational histopathology, promoting precision medicine through exceptional visual decoding abilities. Meningiomas, the most prevalent primary intracranial tumors, necessitate accurate grading and classific...

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Bibliographic Details
Main Authors: Jannik Sehring, Hildegard Dohmen, Carmen Selignow, Kai Schmid, Stefan Grau, Marco Stein, Eberhard Uhl, Anirban Mukhopadhyay, Attila Németh, Daniel Amsel, Till Acker
Format: Article
Language:English
Published: MDPI AG 2023-10-01
Series:Cancers
Subjects:
computational histopathology
deep neural networks
DNA methylome
meningioma
multiple-instance learning
Online Access:https://www.mdpi.com/2072-6694/15/21/5190

Internet

https://www.mdpi.com/2072-6694/15/21/5190

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