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Abstract #3483

MRI based IDH and grade prediction using convolutional neural networks

Sumeet Shinde1, Abhilasha Indoria2, Jitender Saini2, Manish Beniwal2, Vani Santosh2, and Madhura Ingalhalikar1
1Symbiosis centre for medical image analysis, Symbiosis International University, Pune, India, 2Dept of Radiology, National Institute of Mental Health and Neurosciences, Bengaluru, India

Recent developments in glioma subtyping suggest that IDH genotype as well as the histological grading are both crucial factors. However, earlier classification studies based on MRI features have focused either only on grade or IDH. In this work we employ an automated deep learning based technique to delineate the grade as well as the IDH status on a dataset of 178 subjects. Our classifier performs with a superior accuracy of 93.5% and the model explanability is achieved through class activation maps that illustrate the areas important in the classification.

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