Prediction of glioma-subtypes: comparison of performance on a DL classifier using bounding box areas versus annotated tumors

Prediction of glioma-subtypes: comparison of performance on a DL classifier using bounding box areas versus annotated tumors

Abstract Background For brain tumors, identifying the molecular subtypes from magnetic resonance imaging (MRI) is desirable, but remains a challenging task. Recent machine learning and deep learning (DL) approaches may help the classification/prediction of tumor subtypes through MRIs. However, most...

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Bibliographic Details
Main Authors: Muhaddisa Barat Ali, Irene Yu-Hua Gu, Alice Lidemar, Mitchel S. Berger, Georg Widhalm, Asgeir Store Jakola
Format: Article
Language:English
Published: BMC 2022-05-01
Series:BMC Biomedical Engineering
Subjects:
1p/19q codeletion
IDH genotype
Brain tumor
Ellipse bounding box
Deep learning
Online Access:https://doi.org/10.1186/s42490-022-00061-3

Internet

https://doi.org/10.1186/s42490-022-00061-3

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