Riedel N, De Faria FW, Walter C, Bruder JM, Kerl K. Tumor-brain-organoids as a model for pediatric brain tumors research. Neuro-Oncology. 2022;24(Suppl 1):170–170.

Article  Google Scholar 

Gruhle M, Nemes K, Steinbügl M, Johann PD, von Luettichau I, Steinborn M, Tippelt S, Fleischhack G, Lehrnbecher T, Bens S, et al. ATRT-14. malignant rhabdoid tumors of cranial nerves–ATRT or extracranial rhabdoid tumor?. Neuro-Oncology. 2022;24 Suppl 1:i5–i6.

Srinivasa R, Chenna R. MRI brain tumor segmentation and prediction using modified region growing and adaptive SVM. Soft Comput. 2021;25:4135–48.

Article  MATH  Google Scholar 

Polepaka S, Rao CS, Chandra Mohan M. IDSS-based two stage classification of brain tumor using SVM. Health Technol. 2020;10(1):249–58.

Article  MATH  Google Scholar 

Olakkengil SM, Prathima M, et al. Brain image fusion using DWT and Laplacian pyramid approach and tumor detection using watershed segmentation. Int J Adv Eng Manage Sci. 2016;2(5).

Widhiarso W, Pratama I, et al. Combination of DWT variants and GLCM as a feature for brain tumor classification. In: 2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI), IEEE. 2021. p. 197–202.

Saii M, Kraitem Z. Automatic brain tumor detection in MRI using image processing techniques. Biomed Stat Inform. 2017;2(2):73–6.

Google Scholar 

Gandhi BS, Rahman SAU, Butar A, Victor A. Brain tumor segmentation and detection in magnetic resonance imaging (MRI) using convolutional neural network, in: Brain Tumor MRI Image Segmentation Using Deep Learning Techniques, Elsevier. 2022. p. 37–57.

Molachan N, Manoj K, Dhas DAS. Brain tumor detection that uses CNN in MRI. In: 2021 Asian Conference on Innovation in Technology (ASIANCON), IEEE, 2021. p. 1–7.

Alyami J, Rehman A, Almutairi F, Fayyaz AM, Roy S, Saba T, Alkhurim A. Tumor localization and classification from MRI of brain using deep convolution neural network and Salp swarm algorithm. Cogn Comput. 2024;16(4):2036–46.

Article  Google Scholar 

Zhang J, Shen X, Zhuo T, Zhou H. Brain tumor segmentation based on refined fully convolutional neural networks with a hierarchical dice loss. arXiv preprint arXiv:1712.09093 2017

Mathew J, Srinivasan N. Deep convolutional neural network with transfer learning for automatic brain tumor detection from MRI. In: 2022 International Conference on Computing, Communication, Security and Intelligent Systems (IC3SIS), IEEE. 2022. p. 1–6.

Kokila B, Devadharshini M, Anitha A, Sankar SA. Brain tumor detection and classification using deep learning techniques based on MRI images. In: Journal of Physics: Conference Series, Vol. 1916, IOP Publishing. 2021. p. 012226.

Han K, Wang Y, Guo J, Tang Y, Wu E. Vision GNN: an image is worth graph of nodes. In: 6th Conference on Neural Information Processing Systems (NeurIPS 2022). 2022

Amjad R, Attique KM, Tanzila S, Zahid M, Noor A. Microscopic brain tumor detection and classification using 3d CNN and feature selection architecture. Microscopy Research and Technique 2020.

Sadat FM, Wasfy M. Brain tumor grade classification using LSTM neural networks with domain pre-transforms. 2021

Amin AJ, Sharif AM, Gul BN, Yasmin AM, Shad CSA. Brain tumor classification based on dwt fusion of MRI sequences using convolutional neural network. Pattern Recognit Lett. 2020;129:115–22.

Article  Google Scholar 

Tummala S, Kadry S, Bukhari SAC, Rauf HT. Classification of brain tumor from magnetic resonance imaging using vision transformers ensembling. Curr Oncol. 2022;29(10):7498–511.

Article  Google Scholar 

Ashley S. Human visualization of brain tumor classifications using deep CNN: Xception + bigru. Am J Psychiatry Neurosci. 2021;9(4):147–56.

Article  MATH  Google Scholar 

Lee Y, Kang P. AnoViT: unsupervised anomaly detection and localization with vision transformer-based encoder-decoder. IEEE Access. 2022;10:46717–24.

Article  Google Scholar 

Liu Z, Lin Y, Cao Y, Hu H, Wei Y, Zhang Z, Lin S, Guo B. Swin transformer: hierarchical vision transformer using shifted windows. In: Proceedings of the IEEE/CVF international conference on computer vision. 2021. p. 10012–10022.

Kipf TN, Welling M. Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 2016

Chang L, Branco P. Graph-based solutions with residuals for intrusion detection: the modified e-graphsage and e-resgat algorithms. arXiv preprint arXiv:2111.13597 2021

Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Kaiser Ł, Polosukhin I. Attention is all you need. Adv Neural Inf Process Syst. 2017;30:5998–6008.

Google Scholar 

Xu K, Hu W, Leskovec J, Jegelka S. How powerful are graph neural networks?, arXiv preprint arXiv:1810.00826 2018

Cheng J. Brain tumor dataset 2017

Fernando, Brain tumor MRI images 44 classes 2023

Cheng J, Huang W, Cao S, Yang R, Yang W, Yun Z, Wang Z, Feng Q. Correction: enhanced performance of brain tumor classification via tumor region augmentation and partition. PloS ONE. 2015;10(12): e0144479.

Article  MATH  Google Scholar 

Zhou Y, Li Z, Zhu H, Chen C, Gao M, Xu K, Xu J. Holistic brain tumor screening and classification based on densenet and recurrent neural network. In: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries: 4th International Workshop, BrainLes 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers, Part I 4, Springer. 2019. p. 208–217.

Ismael MR, Abdel-Qader I, Brain tumor classification via statistical features and back-propagation neural network, in,. IEEE international conference on electro/information technology (EIT). IEEE. 2018;2018:0252–7.

Abiwinanda N, Hanif M, Hesaputra ST, Handayani A, Mengko TR. Brain tumor classification using convolutional neural network, in: World Congress on Medical Physics and Biomedical Engineering 2018: June 3-8, 2018, Prague, Czech Republic (Vol. 1), Springer. 2019. p. 183–189.

Afshar P, Mohammadi A, Plataniotis KN, Brain tumor type classification via capsule networks. In,. 25th IEEE international conference on image processing (ICIP). IEEE. 2018;2018:3129–33.

Rehman A, Naz S, Razzak MI, Akram F, Imran M. A deep learning-based framework for automatic brain tumors classification using transfer learning. Circuits Syst Signal Process. 2020;39:757–75.

Article  MATH  Google Scholar 

Kaplan K, Kaya Y, Kuncan M, Ertunç HM. Brain tumor classification using modified local binary patterns (LBP) feature extraction methods. Med Hypotheses. 2020;139.

Ghassemi N, Shoeibi A, Rouhani M. Deep neural network with generative adversarial networks pre-training for brain tumor classification based on MR images. Biomed Signal Process Control. 2020;57.

Ayadi W, Elhamzi W, Charfi I, Atri M. Deep CNN for brain tumor classification. Neural Process Lett. 2021;53:671–700.

Article  Google Scholar 

Amou MA, Xia K, Kamhi S, Mouhafid M. A novel MRI diagnosis method for brain tumor classification based on CNN and Bayesian optimization. Healthcare. 2022;10(3):494.

Article  Google Scholar 

Tummala S, Kadry S, Bukhari SAC, Rauf HT. Classification of brain tumor from magnetic resonance imaging using vision transformers ensembling. Curr Oncol. 2022;29(10):7498–511.

Article  Google Scholar 

AVishwakarma M, Elhamzi W. Deep CNN for brain tumor classification. Neural Process Lett. 2021;671–700.

Vishwakarma M. Segmentation and detection of brain tumors using efficientnetb3 model. 2023 2nd International Conference on Automation, Computing and Renewable Systems. 2023. p. 1463–1470.

Rahman MA, Ghosh A, Rahman MS, Siddique MAB. A comparative analysis and visualizable of MRI image type-based brain tumor classification using transfer learning models. In: 2024 6th International Conference on Electrical Engineering and Information and Communication Technology. 2024. p. 7–12.

Priyadarshini P, Kanungo P, Kar T. Multigrade brain tumor classification in MRI images using fine-tuned efficientnet. Prime-Advances Electr Eng Electron Energy. 2024;8(100498).