A decision support system for multimodal brain tumor classification using deep learning

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A Comprehensive Survey on Transfer Learning

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Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

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A Deep Learning-Based Framework for Automatic Brain Tumors Classification Using Transfer Learning

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Comparative analysis of Brain Tumor Categorization on MR Images using various Deep Learning models

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A Survey on Brain Tumor Segmentation Using Deep Learning Techniques

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A UNIFIED PARADIGM OF CLASSIFYING GI TRACT DISEASES IN ENDOSCOPY IMAGES USING MULTIPLE FEATURES FUSION

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Enhancing Brain Tumor Classification in Medical Imaging Through Image Fusion and Data Augmentation Techniques

Hajji, T., Douzi, Y., & Masrour, T. (2023) · Lecture notes in networks and systems · doi:10.1007/978-3-031-43520-1_22 · Cited by 1

Brain Tumour Ordering Using Visual Geometry Group Network

Balabantaray, S., Rath, M., Samal, T., & Mishra, M. R. (2023) · International Conference on Self Sustainable Artificial Intelligence Systems (ICSSAS) · doi:10.1109/icssas57918.2023.10331783 · Cited by 1

A Hybrid Machine Learning Approach for Brain Tumor Classification Using Artificial Neural Network and Particle Swarm Optimization

Dandıl, E. (2023) · Communications in computer and information science · doi:10.1007/978-3-031-50920-9_28 · Cited by 1

Brain Tumor Classification using Hybrid K-means and PSO Approach

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Tree hierarchical deep convolutional neural network optimized with sheep flock optimization algorithm for sentiment classification of Twitter data

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Subclass Classification of Gliomas Using MRI Fusion Technique

Janardhan, K., & Thomas, C. B. (2025) · SN Computer Science · doi:10.1007/s42979-025-03705-y · Cited by 1

A Vision Transformer-Based Intelligent System For Brain Tumor Diagnosis

Akinniyi, O., Dixon, J., Khalifa, F., Saleh, G. A., & Deabes, W. A. (2025) · Lecture notes in networks and systems · doi:10.1007/978-3-031-82377-0_52 · Cited by 1

Optimizing 3D U-Net for Brain MRI Segmentation: MARCOS and MAIRCA-Based Hyperparameter Tuning

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Mapping Research Trends in Deep Learning for Brain Tumor Classification: A Bibliometric Analysis

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Analysis of Biomedical Images Through Deep Learning Model for the Identification of Diseases

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Fine-Tuning Pre-trained Convolutional Neural Network Deep Transfer Learning for Brain Tumor Classification Using Magnetic Resonance Images

Jui, F. I., Kashem, M. A., Islam, M. M., & Uddin, J. (2025) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-031-92625-9_1 · Cited by 1

Fake News Detection With Credibility Scoring on Turkish Twitter Data

Aydın, Ö., Öztürk, E., & Kantarcı, H. (2025) · IEEE Access · doi:10.1109/access.2025.3594010 · Cited by 1

Novel BDefRCNLSTM: an efficient ensemble deep learning approaches for enhanced brain tumor detection and categorization with segmentation

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Automated Brain Tumor MRI Segmentation Using ARU-Net with Residual-Attention Modules

Özbay, E., & Ozbay, F. A. (2025) · Diagnostics · doi:10.3390/diagnostics15182326 · Cited by 1

BrainNet: a custom-designed CNN and transfer learning-based models for diagnosing brain tumors from MRI images

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Deep Learning Advances for Brain Tumor Diagnosis and Multimodal MRI Registration

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Hybrid deep neural network with PCA based features optimization for enhancing brain tumor classification

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Interpretable Deep Learning for Multiclass Brain Tumor Classification Using MRI and LIME

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Deep Learning Based Brain Tumor Diagnosis

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MTA-Swin: A Multi-Token Attention Swin Transformer for Brain Tumor Classification with Leakage-Free MRI Benchmarking

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AUTOMATED ACCIDENTS ON ROAD ANALYSIS: AN OVERVIEW OF STATE OF THE INSIGHTS

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Hybrid deep learning algorithm for brain tumour detection

Srivastava, J., Prakash, J., & Srivastava, A. K. (2022) · The Imaging Science Journal · doi:10.1080/13682199.2023.2167624 · Cited by 1

Detection of Brain Tumors Using Magnetic Resonance Images through the Application of an Innovative Convolution Neural Network Model

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Transformation of MRI Images to Three-Level Color Spaces for Brain Tumor Classification Using Deep-Net

Dahan, F. (2024) · Intelligent Automation & Soft Computing · doi:10.32604/iasc.2024.047921 · Cited by 1

Transforming 3D Brain Tumour Image Segmentation: An Enhanced V-Net Approach for Precise Diagnosis and Treatment Planning

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A Linear Time Shrinking-SL(t)-ViT Approach for Brain Tumor Identification and Categorization

Swetha, A. V. S., Bala, M., & Sharma, K. (2024) · IETE Journal of Research · doi:10.1080/03772063.2024.2370954 · Cited by 1

Brain Tumor Detection via Transfer Learning and Ensemble Learning

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Early Brain Tumor Prediction Using Hybrid Optimized Fuzzy Clustering-Active Contour Segmentation Based Heuristic Deep Learning Model

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Brain tumor detection using hybrid transfer learning and patch antenna-enhanced microwave imaging

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Leveraging explainable AI in deep learning for brain tumor detection

Kothadiya, D., Chaudhari, A., Faldu, P., & Gajjar, D. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-23979-3.00014-2 · Cited by 1

Optimizing Brain Tumor Classification with GridSearchCV Using Multimodal Image Fusion: A Hyperparameter Tuning Approach

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A Proposed Deep Learning Approach for Brain Tumor Classification from MRI Images

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Robust Brain Diseases Classification Using CNN and Soft Computing Techniques

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ML_BrainDetection: An Intelligent Model for Brain Tumor Identification Using Machine Learning

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Automatic Tracking of Muscle Fiber Direction in Ultrasound Images Based on Improved Kalman Filter

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An Optimized Transfer Learning Based Framework for Brain Tumor Classification

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A Review of Current Approaches to Automated Detection of Malignant Tumors Based on MR Images

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Data Augmentation with Image Fusion Techniques for Brain Tumor Classification using Deep Learning

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Efficient Brain Tumor Classification Technique Based on Convolutional Neural Network

Maurya, B., & Hiranwal, S. (2023) · Algorithms for intelligent systems · doi:10.1007/978-981-99-3485-0_26

An Efficient Pre-Trained Classification of Brain Tumor with Convolutional Neural Networks

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Review on Brain Tumor Segmentation and Classification using Artificial Intelligence

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Systematic study and design of multimodal MRI image augmentation for brain tumor detection with loss aware exchange and residual networks

Bhuyan, R. K., & Nandi, G. (2023) · International Journal of Imaging Systems and Technology · doi:10.1002/ima.22989

Deep Learning Based CAD System for Early Detection of Brain Tumor

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DTDO: Driving Training Development Optimization enabled deep learning approach for brain tumour classification using MRI

Prasad, V. V. K. D. V., Jingle, I. D. J., & Sriramakrishnan, G. V. (2024) · Network Computation in Neural Systems · doi:10.1080/0954898x.2024.2351159

Automated brain disorder diagnosis using invasive weed optimization with deep learning on magnetic resonance images

Uvaneshwari, M., & Baskar, M. (2024) · AIP conference proceedings · doi:10.1063/5.0217029

Brain Tumor Classification Using LBP-TOPs from 3D MRI Images

Naqvi, N. Z., & Seeja, K. R. (2024) · Lecture notes in networks and systems · doi:10.1007/978-981-97-6106-7_27

Advanced Machine Learning for Brain Tumor and Alzheimer’s Disease Detection: A Comprehensive Review of Neuroimaging-based Classification Techniques

Kumar, N., Narawade, V. E., Chheda, K., Patkar, H., & Mishra, A. (2024) · Advances in Artificial Intelligence Research · doi:10.54569/aair.1582085

Improved Skin Lesion Classification Using Gaussian Filtering and Mobile Net-Based Convolutional Neural Networks

Khan, S. A., Raza, A., Anwar, M., & Siddiqui, O. A. (2024) · Global Conference on Wireless and Optical Technologies (GCWOT) · doi:10.1109/gcwot63882.2024.10805609

Effective Segmentation and Classification of Brain Tumour MRI Images Using YOLOv8 Technique

Taradale, A. P., & Kattimani, S. L. (2024) · International Conference on Innovation and Novelty in Engineering and Technology (INNOVA) · doi:10.1109/innova63080.2024.10847033

Research on Classification and Detection Mechanism of Brain Tumor based on SE-VGG-16

Xie, Y., Zhou, J., Ji, X., Shi, J., & Chen, S. (2024) · International Conference on Electronic Information Technology and Computer Engineering (EITCE) · doi:10.1145/3711129.3711136

MRI Brain Tumour Classification Using Machine Learning and Deep Learning

Muralikrishna, C., & Chandre, S. (2024) · International Conference on Mobile Networks and Wireless Communications (ICMNWC) · doi:10.1109/icmnwc63764.2024.10872321

Modern approaches to segmentation and analysis of brain structures: problems and solutions

Tsygankov, V. A., Kudrin, R. A., Kataev, A., Аркадьевна, Ш. О., & Садовникова, Н. П. (2025) · Vrach i informacionnye tehnologii · doi:10.25881/18110193_2025_1_42

ECFO-DCNN: Egocentric Critter Fish Optimization Enabled Deep Convolutional Neural Network for Brain Tumor Classification

Potadar, M. P., Holambe, R. S., & Chile, R. H. (2025) · Biomedical Materials & Devices · doi:10.1007/s44174-025-00311-7

Lung Cancer Detection Using Image Processing

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Brain Tumor Prediction Using Transfer Learning and Light-Weight Deep Learning Architectures

Wani, M. A., Sultan, B., Ali, S., & Sofi, M. A. (2025) · Studies in big data · doi:10.1007/978-981-96-3498-9_13

Brain Tumor Classification Using Deep Learning Techniques

Bhutani, M., Kansotia, A., Akanksha, A., & Naqvi, N. Z. (2025) · Lecture notes in networks and systems · doi:10.1007/978-981-96-3372-2_1

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Rashika, R. S., Sam, D., Nataraj, K., & Gayathri, A. (2024) · Intelligent Decision Technologies · doi:10.1177/18724981241291460

LiteVessel : In‐Depth Exploration of Lightweight Deep Neural Network Models for Retinal Vessel Segmentation

Alharthi, R. S., Alhussein, M. A., Fareed, K., Islam, M., & Aurangzeb, K. (2025) · International Journal of Imaging Systems and Technology · doi:10.1002/ima.70145

Optimizing Brain Tumor Classification with ViT: A Metaheuristic Approach

Vishnupriya, S., & Sakthisudhan, K. (2025) · Journal of Electrical Engineering and Technology · doi:10.1007/s42835-025-02329-9

Evaluating the Detection of Small Brain Lesions in Magnetic Resonances Using Deep LearningPreprint

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Deep Learning Architectures for Brain Tumor Classification: A Comprehensive Investigation of Advances, Challenges and Clinical Translation

Wang, C. (2025) · Science and Technology of Engineering Chemistry and Environmental Protection · doi:10.61173/0ahc4e18

Hybrid Deep Learning and Machine Learning for Brain Tumor Detection: CNN Meets Random Forest

Yashu, Y., & Kukreja, V. (2025) · International Conference for Emerging Technology (INCET) · doi:10.1109/incet64471.2025.11140876

Performance Enhancement of CNN and LSTM Models for Brain Tumor Detection with GA and PSO Optimization

Nandhinidevi, S., Harini, P., Kabisa, P., & Haridha, M. (2025) · International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC) · doi:10.1109/assic64892.2025.11157978

Enhanced Medical Diagnosis Using Multimodal Deep Learning: A Comprehensive approach to Data Fusion and Analysis

Sharma, N., & Sharma, S. (2025) · International Conference on Intelligent Computing and Knowledge Extraction (ICICKE) · doi:10.1109/icicke65317.2025.11136436

MreNet: Multimodal Regularization Ensemble Network for Hierarchical Paper Classification

Yue, T., Shi, X., Zhan, S., Song, Z., & Hu, Z. (2025) · Communications in computer and information science · doi:10.1007/978-981-95-2566-9_15

Hybrid GJOA-HHO Driven Attention U-Net and ICNN for Brain Tumor Detection

Alphonsa, J., & Kumari, V. S. (2025) · International Conference on Emerging Techniques in Computational Intelligence (ICETCI) · doi:10.1109/icetci67340.2025.11258046

Brain Tumour Classification Model Based on Spatial Block–Residual Block Collaborative Architecture with Strip Pooling Feature Fusion

Tang, M., Zhou, X., & Li, Z. (2025) · Journal of Imaging · doi:10.3390/jimaging11120427

Evaluating Deep vs Lightweight: ResNet50V2 and MobileNetV2 in Meningioma Detection

Femila Irene, G., & Surendran, R. (2025) · Asian Conference on Innovation in Technology (ASIANCON) · doi:10.1109/asiancon66527.2025.11281082

Improved Deep Joint Segmentation with Enhanced Feature Set for Cervical Spine Fracture Classification

Raju, K. G., & Ravikumar, S. (2025) · Biomedical Materials & Devices · doi:10.1007/s44174-025-00597-7

Convolution Neural Networks

Bhagyalaxmi, K., & Dwarakanath, B. (2025) · Springer proceedings in mathematics & statistics · doi:10.1007/978-3-031-51342-8_12

Brain tumor detection using deep learning in the field of healthcare

Panda, S., Akhil, Satapathy, S. S., Shandilya, P., Malik, M., Saha, R., & Kumar, N. (2025) · AIP conference proceedings · doi:10.1063/5.0296699

Enhanced brain tumor classification using modified Resnet50v2 with data augmentation techniques

Chandralekha, E., Mariyarose, J. V., Veerasamy, K., Ayyappa, Y., Subburam, R. K., & Benjamin, M. I. S. W. (2026) · AIP conference proceedings · doi:10.1063/5.0298227

Healthcare Intelligent Technologies for Real-Time Brain Anomaly Detection

Цыганков, В., Kataev, A., Kudrin, R. A., Orlov, D. V., & Berestneva, O. G. (2026) · Communications in computer and information science · doi:10.1007/978-3-032-14674-8_48

Brain Tumor Classification using MRI Images with CNN and SVM Classifiers

A, D. H., Jain, B., S, N. F. H., R, A. U., S, P. H., & I, A. S. (2025) · International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT) · doi:10.1109/icerect65215.2025.11375877

An Empirical Analysis of Various Techniques for Brain Tumor Classification using MRI Images

Nisha, M., & Kumar, R. N. D. (2025) · International Conference on NexGen Networks and Cybernetics (IC2NC) · doi:10.1109/ic2nc67409.2025.11376370

Multiclass Brain Tumor Classification using Optimization Enabled Deep Learning

Jarria, S. P. A., & Wesley, A. B. (2025) · International Conference on NexGen Networks and Cybernetics (IC2NC) · doi:10.1109/ic2nc67409.2025.11376428

MM FD ConvFormer multimodal frequency aware deformable CNN transformer network for robust brain tumor classification

Selvarathinam, A. L. X. R. A., Lilhore, U. K., Alroobaea, R., Alsafyani, M., Baqasah, A. M., Algarni, S. A., & Khan, M. M. (2026) · Scientific Reports · doi:10.1038/s41598-026-43616-3

Red nucleus region segmentation-based brain tumor classification and stage estimation using GLRN-SGNet and Deep-2C-MHONN

Gugulothu, V. K. (2026) · Multimedia Tools and Applications · doi:10.1007/s11042-026-21201-0

Deep learning techniques for brain tumor detection and classification: trends, challenges, and future directions

Santhosh, A. J. S., Lingaswamy, S., & Ramamurthy, K. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-41459-6.00006-7

Enhanced Brain Tumor Detection Using GoogLeNet: A Deep Learning Approach for MRI-Based Diagnostics

Manoj Sudeep, D., & Saladi, S. (2025) · International Conference on Recent Trends in Electrical, Electronics and Computing Technologies (ICRTEECT) · doi:10.1109/icrteect67512.2025.11448760

Real-Time Detection Transformer Model Based Brain Tumor Detection and Classification Using MRI Image Analysis

Kumar, D. S., & Nandan, D. (2026) · IEEE International Conference on Emerging Computing and Intelligent Technologies (ICoECIT) · doi:10.1109/icoecit68303.2026.11497877

Towards Decentralized Brain Tumor Classification Using Federated Learning with Explainable AI

Mahadi, M. H., Prity, F. S., Rahman, S. M. A., Abdullah, Y., Ahmed, M. S., & Chayon, M. H. R. (2025) · International Conference on Computer and Information Technology (ICCIT) · doi:10.1109/iccit68739.2025.11490360

ICDMS: Integrating multimodal data for intelligent clinical decision-making in healthcare: Current trends and future directions

Shehnaz, Ahamed, J., Albaqami, A., & Nisa, K. U. (2026) · Scottish Medical Journal · doi:10.1177/00369330261449407

Ensemble Deep Learning for Brain Tumor Detection: Integrating InceptionV3 and MobileNetV3 Models on MRI Scans

Abid, M. A. S., Suleman, M. N., Chowdhury, P., Razzak, R. B., & Afrin, T. (2025) · IEEE International Conference on Signal Processing, Information, Communication and Systems (SPICSCON) · doi:10.1109/spicscon69221.2025.11504404

ViTGradX: An Explainable Vision Transformer Framework and Deep Survival Modeling for Multimodal Brain Tumor Classification and Prognosis

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