1. Abiwinanda, N., Hanif, M., Hesaputra, S.T., Handayani, A., Mengko, T.R.: Brain tumor classification using convolutional neural network. In: World congress on medical physics and biomedical engineering 2018, pp. 183–189. Springer (2019)
2. Banerjee, S., Mitra, S., Masulli, F., Rovetta, S.: Deep radiomics for brain tumor detection and classification from multi-sequence mri. arXiv preprint arXiv:1903.09240 (2019)
3. Banerjee, S., Mitra, S., Masulli, F., Rovetta, S.: Deep radiomics for brain tumor detection and classification from multi-sequence mri. arXiv preprint arXiv:1903.09240 (2019)
4. Cornelius, J.F., Slotty, P.J., Steiger, H.J., Hänggi, D., Polivka, M., George, B.: Malignant potential of skull base versus non-skull base meningiomas: clinical series of 1,663 cases. Acta Neurochirurgica 155(3), 407–413 (2013)
5. Dai, Z., Liu, H., Le, Q.V., Tan, M.: Coatnet: marrying convolution and attention for all data sizes. Adv. Neural Inf. Process. Syst. 34, 3965–3977 (2021)