Brain Tumor Detection Based on Multimodal Information Fusion and Convolutional Neural Network

ImageNet classification with deep convolutional neural networks

Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155

Backpropagation Applied to Handwritten Zip Code Recognition

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The multimodal brain tumor image segmentation benchmark (BRATS)

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Brain tumor segmentation with Deep Neural Networks

Havaei, M., Davy, A., Warde-Farley, D., Biard, A., Courville, A., Bengio, Y., Pal, C., Jodoin, P.-M., & Larochelle, H. (2017) · Medical Image Analysis · doi:10.1016/j.media.2016.05.004 · Cited by 3,278

Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images

Pereira, S., Pinto, A., Alves, V., & Silva, C. A. (2016) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2016.2538465 · Cited by 2,735

A deep learning model integrating FCNNs and CRFs for brain tumor segmentation

Zhao, X., Wu, Y., Song, G., Li, Z., Zhang, Y., & Fan, Y. (2018) · Medical Image Analysis · doi:10.1016/j.media.2017.10.002 · Cited by 813

Automatic segmentation of non-enhancing brain tumors in magnetic resonance images

Fletcher-Heath, L., Hall, L., Goldgof, D. B., & Murtagh, F. R. (2001) · Artificial Intelligence in Medicine · doi:10.1016/s0933-3657(00)00073-7 · Cited by 294

Neural Network Based Brain Tumor Detection Using Wireless Infrared Imaging Sensor

Mohamed Shakeel, P., Tobely, T. E. E., Al-Feel, H., Manogaran, G., & Baskar, S. (2019) · IEEE Access · doi:10.1109/access.2018.2883957 · Cited by 232

Comparison of normalization methods for the analysis of metagenomic gene abundance data

Pereira, M. B., Wallroth, M., Jönsson, V., & Kristiansson, E. (2018) · BMC Genomics · doi:10.1186/s12864-018-4637-6 · Cited by 197

Brain tumor detection and classification: A framework of marker‐based watershed algorithm and multilevel priority features selection

Khan, M. A., Lali, M. I. U., Rehman, A. U., Ishaq, M., Sharif, M. I., Saba, T., Zahoor, S., & Akram, T. (2019) · Microscopy Research and Technique · doi:10.1002/jemt.23238 · Cited by 186

Convolutional Neural Network with Segmentation in Brain Tumour Diagnosis: An extensive review

Shahi, M., Alsadoon, O. H., & AlSallami, N. (2020) · International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA) · doi:10.1109/citisia50690.2020.9371858 · Cited by 1

An Improved Deep Neural Learning Classifier for Brain Tumor Detection

Kurian, S. M., & Juliet, S. (2022) · International Conference on Computing Methodologies and Communication (ICCMC) · doi:10.1109/iccmc53470.2022.9754022 · Cited by 1

Deep learning based Brain Tumour Classification based on Recursive Sigmoid Neural Network based on Multi-Scale Neural Segmentation

Ibrahim, S., & Ravi, G. (2023) · International Journal on Recent and Innovation Trends in Computing and Communication · doi:10.17762/ijritcc.v11i2s.6031 · Cited by 1

Identification and Detection of Tumour Hypoxia from Multimodal Microscopy using Deep Neural NetworkPreprint

Mahalingam, D. U., & Prittopaul, P. (2020) · SSRN Electronic Journal · doi:10.2139/ssrn.3554914

Identifying Tumor by Segmentation of Brain Images Using Combinatory Approach of Convolutional Neural Network and Biogeography Algorithm

Dehariya, A. K., & Shukla, P. (2021) · Algorithms for intelligent systems · doi:10.1007/978-981-16-2248-9_8

BT Classification Using Deep Learning Techniques from MRI Images—A Review

Neethu, M. S., & Jayasingh, J. R. (2023) · Lecture notes in electrical engineering · doi:10.1007/978-981-19-8338-2_15

Brain tumor segmentation of MR images using deep learning techniques: A review

Mandle, A. K., Sahu, S. P., & Gupta, G. P. (2023) · AIP conference proceedings · doi:10.1063/5.0133108

Enhanced approach for brain tumor detection

Mar, K., Vinuta, P., Sushitha, R., Hepseeba, G., & Martha, B. (2023) · i-manager’s Journal on Image Processing · doi:10.26634/jip.10.2.19818

Analysis of Brain Tumor Detection Techniques

Das, A., Jangde, M. K., & Bhattacharya, M. D. (2023) · International Journal for Research in Applied Science and Engineering Technology · doi:10.22214/ijraset.2023.55133

Optimizing Precision: Brain Tumor Detection

Rai, P. N., Supekar, P. V., Shaikh, S. S., Sawant, S. S., & Shinde, A. V. (2023) · International Journal for Research in Applied Science and Engineering Technology · doi:10.22214/ijraset.2023.56477

A deep learning-based intelligent decision-making model for tumor and cancer cell identification

Durga, P., & Godavarthi, D. (2023) · Bulletin of Electrical Engineering and Informatics · doi:10.11591/eei.v13i1.6469

A Study on Effective Segmentation Network in MRI Images for Diagnosis of Brain Tumor

Singha, A., & Vanitha, V. (2023) · IEEE International Conference on Computer Vision and Machine Intelligence (CVMI) · doi:10.1109/cvmi59935.2023.10464985

Machine Learning Based Intelligent Diagnosis of Brain Tumor: Advances and Challenges

Panda, S. K., Barik, R. C., Pelusi, D., & Panda, G. (2024) · Intelligent systems reference library · doi:10.1007/978-3-031-54038-7_11

Unet-Cbam Guided Deep Learning for Enhanced Brain Tumor ClassificationPreprint

ADRIAN, A. U. R., & George Chellin Chandran, J. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4789509

Brain Tumour Detection and Classification using Deep Convolutional Neural Network (DCNN)

Babu, M. N., Balakrishna, A., Yasasri, G., Siva, C. S., & Vamsi, P. M. (2024) · International Journal of Scientific Research in Computer Science Engineering and Information Technology · doi:10.32628/cseit2410288

Design of English Lexical Analysis System for Machine Translation Based on Multimodal Neural Network

Deng, Y., & Shi, J. (2024) · International Journal of High Speed Electronics and Systems · doi:10.1142/s0129156424400366

Comparison of Clustering Algorithms for Segregating the Planar Sections of Brain Tumour MRIs

Jhariya, A., Parekh, D., Lobo, J., Mogal, A., Bongale, A. M., & Jayaswal, R. (2024) · MIT Art, Design and Technology School of Computing International Conference (MITADTSoCiCon) · doi:10.1109/mitadtsocicon60330.2024.10575146

Advances in Brain Tumor Detection and Localization

Paul, K., Patra, A., & Paul, P. (2024) · doi:10.1002/9781394270910.ch8

Implementation of Morphological Fractional Order Darwinian Operator for Brain Tumour Localization

Ansah, K., Adevu, W. B., Mensah, J. A., & Appati, J. K. (2024) · Communications in computer and information science · doi:10.1007/978-3-031-72483-1_13

Techniques and Features Analysis on COVID-19 X-Ray Image

Singh, P., & Veenadhari, S. (2024) · Advances in computer and electrical engineering book series · doi:10.4018/979-8-3693-6875-6.ch018

Nonlinear activation functions of convolutional neural networks for classification of brain tumors using magnetic resonance imaging

Wahlang, I., & Maji, A. K. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-13816-4.00014-0

Enhancing Brain Tumour Detection and Classification: Comparative Analysis of Deep Learning ANN Models

Nidhi, R., Bhagyashree, A. M., Kodipalli, A., Rao, T., Rohini, B. R., & Gargi, N. (2024) · International Conference on Integrated Intelligence and Communication Systems (ICIICS) · doi:10.1109/iciics63763.2024.10859349

A comprehensive review on deep learning approaches for brain tumour classification and prediction: Current status and future prospects

Jadhav, R. N., & Govindaswamy, S. (2025) · AIP conference proceedings · doi:10.1063/5.0247026

Reconstruction, Identification, Classification and Segmentation of Brain Tumor Using GAN and Faster R-CNN

K, A. A., Sravya, A., VenkatAkhil, R., & Veena, M. B. (2025) · INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT · doi:10.55041/ijsrem44019

Hybrid Machine Learning Model with Textural Feature Analysis for Brain Tumour Detection

Sharma, A., & Arora, S. (2024) · Global AI Summit - International Conference on Artificial Intelligence and Emerging Technology (AI Summit) · doi:10.1109/globalaisummit62156.2024.10947920

Application of AI to Detect Brain Tumors

Kalita, K., Mall, P., & Raina, D. (2025) · Springer eBooks · doi:10.1007/978-981-96-4241-0_15

Brain Tumor Detection Techniques: A Review

Thour, R., & Kaur, M. (2025) · INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT · doi:10.55041/ijsrem41147

CNN-Based Detection of Brain Tumors Using Multimodal MRI Images

Harshid, K., Diyaneswaran, D., Sanal, M., & Maheshwari, S. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-08253-4_50

Brain Tumor Detection from MRI Images Using YOLOv8 Deep Learning Model

Patil, V. R., Vaidya, A. S., & Patil, M. S. (2026) · International Journal of Advancement and Innovation in Technology and Research · doi:10.63844/ijaitr.v3.i1.2026.142-146

Brain MRI Classification Technique using the VGG16 and Grid Search Optimized SVM

Jha, C. K. (2025) · International Conference on Communication and Smart Devices (ICCoSD) · doi:10.1109/iccosd66074.2025.11348464

Contrast-enhanced MRI segmentation and classification with optimized vector machine classifier

Asiri, A. A. M., Soomro, T. A., Ubaid, F. B., Jandan, F. A., Irfan, M., Mehdar, K. M., Alelyani, M., Alshuhri, M. S., Alghamdi, A., & Alamri, S. (2026) · PeerJ Computer Science · doi:10.7717/peerj-cs.3482

An Enhanced MRI-Based Model for Brain Tumor Classification Using Fine-Tuned InceptionV3

Kathuria, A., Gupta, D., & Uppal, M. (2026) · Lecture notes in electrical engineering · doi:10.1007/978-981-95-6063-9_11

Robust MRI Image Segmentation: Leveraging the Power of KGM Optimized W-FCM with Deep Learning

Anantharajan, S., Gunasekaran, S., Anantharajan, S., & Subramanian, T. (2026) · SN Computer Science · doi:10.1007/s42979-026-05075-5

Brain Tumor Detection and Classification with Pretrained CNNs

Verma, T., Gorak, T., Anisha, P. R., & Paskaran, M. K. (2025) · International Conference on Information Management & Machine Intelligence (ICIMMI) · doi:10.1145/3793449.3793490

Multi-Class Brain Tumour Detection from MRI Images Using Fine-Tuned Deep Learning Models

Onapakala, K., Anitha, A., Nandi, S., Jain, N., Gupta, D., Gupta, A., & Sharma, S. (2026) · International Conference on Computational Intelligence and Communication Networks (CICN) · doi:10.1109/cicn70047.2026.11594248

Classification of Brain Tumours Using Multimodal Driven Deep Learning Techniques

Deepthi, D., & Krishna, P. R. (2025) · Indian Conference on Computer Vision, Graphics and Image Processing · doi:10.1145/3774521.3774544

Multimodal brain tumor detection from fine grained brain image data using lightweight rex spatial multi-scale dual attention single candidate network

Reddy, V. S. K., & Poladi, P. K. (2026) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2026.111266

Automated Brain Tumor Detection & Classification from MRI Using Fine-Tuned Efficientnet-B2 CNN

Thomas, B., P, A. K., S, S. K., Soubhagyalakshmy, P., Johnson, A., & S, S. K. (2026) · International Conference on Innovations in Mechanical, Robotics, Computing and Biomedical Engineering (ICIMRBE) · doi:10.1109/icimrbe70745.2026.11710138

Fusion-Based Multimodal Brain Tumor Detection Using Convolution Neural Network

Banerjee, S., Roy, S., & Das, A. (2021) · Lecture notes in bioengineering · doi:10.1007/978-981-33-6915-3_19

Enhanced Brain Tumor Diagnosis through Multimodal Fusion and 3D Convolutional Neural Networks

J, C. M. B. M., Kannan, E., Alex David, S., Thangarasu, G., & Begum, A. (2023) · International Conference On Smart Technologies For Smart Nation (SmartTechCon) · doi:10.1109/smarttechcon57526.2023.10391443 · Cited by 3

Multi Modal Convolutional Neural Networks for Brain Tumor SegmentationPreprint

Aygün, M. M., Şahin, Y. H., & Ünal, G. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1809.06191 · Cited by 39

Brain Tumor Detection Using Integration of Computed Tomography and Magnetic Resonance Imaging via Fully Convolutional Neural Networks

da Rocha, A. M., Serafim, F. L., & Sousa, A. A. C. (2026) · Journal of Computer Sciences and Informatics. · doi:10.5455/ejcsi.20250919030734

Learning Methods of Convolutional Neural Network Combined With Image Feature Extraction in Brain Tumor Detection

Wang, W., Bu, F., Lin, Z., & Zhai, S. (2020) · IEEE Access · doi:10.1109/access.2020.3016282 · Cited by 74