BrainMRNet: Brain tumor detection using magnetic resonance images with a novel convolutional neural network model

CBAM: Convolutional Block Attention Module

Woo, S., Park, J., Lee, J.-Y., & Kweon, I. S. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-01234-2_1 · Cited by 25,853

SGDR: Stochastic Gradient Descent with Warm Restarts

Loshchilov, I., & Hutter, F. (2016) · arXiv · doi:10.48550/arxiv.1608.03983 · Cited by 5,309

Hypercolumns for object segmentation and fine-grained localization

Hariharan, B., Arbelaez, P., Girshick, R., & Malik, J. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298642 · Cited by 1,511

Multi-grade brain tumor classification using deep CNN with extensive data augmentation

Sajjad, M., Khan, S., Muhammad, K., Wu, W., Ullah, A., & Baik, S. W. (2018) · Journal of Computational Science · doi:10.1016/j.jocs.2018.12.003 · Cited by 895

Adaptive batch normalization for practical domain adaptation

Li, Y., Wang, N., Shi, J., Hou, X., & Liu, J. (2018) · Pattern Recognition · doi:10.1016/j.patcog.2018.03.005 · Cited by 601

Identification and classification of brain tumor MRI images with feature extraction using DWT and probabilistic neural network

Shree, N. V., & Kumar, T. N. R. (2018) · Brain Informatics · doi:10.1007/s40708-017-0075-5 · Cited by 490

A comparison of deep networks with ReLU activation function and linear spline-type methods

Eckle, K., & Schmidt-Hieber, J. (2018) · Neural Networks · doi:10.1016/j.neunet.2018.11.005 · Cited by 414

Residual Networks of Residual Networks: Multilevel Residual Networks

Zhang, K., Sun, M., Han, T. X., Yuan, X., Guo, L., & Liu, T. (2017) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2017.2654543 · Cited by 413

A Deep Feature Learning Model for Pneumonia Detection Applying a Combination of mRMR Feature Selection and Machine Learning Models

Toğaçar, M., Ergen, B., Cömert, Z., & Özyurt, F. (2019) · IRBM · doi:10.1016/j.irbm.2019.10.006 · Cited by 298

BreastNet: A novel convolutional neural network model through histopathological images for the diagnosis of breast cancer

Toğaçar, M., Özkurt, K. B., Ergen, B., & Cömert, Z. (2019) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2019.123592 · Cited by 276

MRI Brain Tumor Classification Using Deep Convolutional Neural Network

Rahman, T., & Islam, M. S. (2022) · International Conference on Innovations in Science, Engineering and Technology (ICISET) · doi:10.1109/iciset54810.2022.9775817 · Cited by 20

Brain tumor image pixel segmentation and detection using an aggregation of GAN models with vision transformer

Datta, P., & Rohilla, R. (2023) · International Journal of Imaging Systems and Technology · doi:10.1002/ima.22979 · Cited by 20

ARiViT: attention-based residual-integrated vision transformer for noisy brain medical image classification

Hameed, M., Zameer, A., Khan, S. H., & Raja, M. A. Z. (2024) · The European Physical Journal Plus · doi:10.1140/epjp/s13360-024-05220-0 · Cited by 20

A successive framework for brain tumor interpretation using Yolo variants

Priyadharshini, S., Bhoopalan, R., Manikandan, D., & Ramaswamy, K. (2025) · Scientific Reports · doi:10.1038/s41598-025-13155-4 · Cited by 19

Intra- and Interpatient ECG Heartbeat Classification Based on Multimodal Convolutional Neural Networks with an Adaptive Attention Mechanism

Paolo, Í. F. D., & CASTRO, A. R. G. (2024) · Applied Sciences · doi:10.3390/app14209307 · Cited by 24

Utilising VGG-16 of Convolutional Neural Network for Medical Image Classification

Ismail, A. R., Nisa, S. Q., Shaharuddin, S. A., Masni, S. I., & Amin, S. A. S. (2024) · International Journal on Perceptive and Cognitive Computing · doi:10.31436/ijpcc.v10i1.460 · Cited by 18

An Intelligent Hybrid Approach for Brain Tumor Detection

Ullah, S., Ahmad, M., Anwar, S., & Khattak, M. I. (2023) · Pakistan Journal of Engineering and Technology · doi:10.51846/vol6iss1pp34-42 · Cited by 17

A Hybrid Deep Learning Framework for Automatic Detection of Brain Tumours Using Different Modalities

Sahu, A., Das, P. K., Paul, I., & Meher, S. (2024) · IEEE Transactions on Emerging Topics in Computational Intelligence · doi:10.1109/tetci.2024.3442889 · Cited by 18

Evaluating Brain Tumor Detection with Deep Learning Convolutional Neural Networks Across Multiple MRI Modalities

Stathopoulos, I., Serio, L., Karavasilis, E., Kouri, M. A., Velonakis, G., Kelekis, N., & EFSTATHOPOULOS, E. P. (2024) · Journal of Imaging · doi:10.3390/jimaging10120296 · Cited by 17

A Novel Deep CNN Model for Classification of Brain Tumor from MR Images

Rai, H. M., Chatterjee, K., Gupta, A., & Dubey, A. K. (2020) · IEEE International Conference for Convergence in Engineering (ICCE) · doi:10.1109/icce50343.2020.9290740 · Cited by 16

Brain Tumor Automatic Detection from MRI Images Using Transfer Learning Model with Deep Convolutional Neural Network

Bayoumi, E. S., Abd-Ellah, M. K., Khalaf, A. A. M., & Gharieb, R. R. (2021) · Journal of Advanced Engineering Trends · doi:10.21608/jaet.2020.42896.1051 · Cited by 16

Local and Deep Features Based Convolutional Neural Network Frameworks for Brain MRI Anomaly Detection

Einy, S., Saygın, H., Hivehch, H., & Navaei, Y. D. (2022) · Complexity · doi:10.1155/2022/3081748 · Cited by 16

Implementing a Novel Low Complexity CNN Model for Brain Tumor Detection

Al-Ani, N. Q., & Al-Shamma, O. (2022) · International Conference on Contemporary Information Technology and Mathematics (ICCITM) · doi:10.1109/iccitm56309.2022.10031630 · Cited by 16

A Robust Brain Tumor Detector Using BiLSTM and Mayfly Optimization and Multi-Level Thresholding

Mahum, R., Sharaf, M. A. F., Hassan, H., Liang, L., & Huang, B. (2023) · Biomedicines · doi:10.3390/biomedicines11061715 · Cited by 16

An Intelligent VGG-16 Framework for Brain Tumor Detection Using MRI-Scans

Shourie, P., Anand, V., & Gupta, S. (2023) · International Conference on Smart Systems for Applications in Electrical Sciences (ICSSES) · doi:10.1109/icsses58299.2023.10200833 · Cited by 16

An explainable ensemble approach for advanced brain tumor classification applying Dual-GAN mechanism and feature extraction techniques over highly imbalanced data

Roy, P., Srijon, F. M. S., & Bhowmik, P. (2024) · PLoS ONE · doi:10.1371/journal.pone.0310748 · Cited by 16

A Deep Learning Based Convolution Neural Network-DCNN Approach to Detect Brain Tumor

Shrestha, H., Dhasarathan, C., Kumar, M., Nidhya, R., Shankar, A., & Kumar, M. (2022) · Advances in intelligent systems and computing · doi:10.1007/978-981-16-6887-6_11 · Cited by 16

An effective hybrid deep learning with adaptive search and rescue for brain tumor detection

S, S. K. H., & Karibasappa, K. (2022) · Multimedia Tools and Applications · doi:10.1007/s11042-022-12474-2 · Cited by 16

An analysis of convolutional neural network and conventional machine learning for multiclass brain tumor detection

Yadav, A., Kumar, R., & Gupta, M. (2024) · AIP conference proceedings · doi:10.1063/5.0198745 · Cited by 15

Current challenges of the state-of-the-art of AI techniques for diagnosing brain tumor

Ahmed, H., Dada, M. O., & Samaila, B. B. (2023) · Material Science & Engineering International Journal · doi:10.15406/mseij.2023.07.00224 · Cited by 15

Agnostic multimodal brain anomalies detection using a novel single-structured framework for better patient diagnosis and therapeutic planning in clinical oncology

Ramaraj, K., Govindaraj, V., Zhang, Y., Murugan, P. R., Wang‎, S., Thiyagarajan, A., & Sankaran, S. (2022) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2022.103786 · Cited by 14

A Review on Multi-organ Cancer Detection Using Advanced Machine Learning Techniques

Sadad, T., Rehman, A. U., Hussain, A., Abbasi, A. A., & Khan, M. Q. (2020) · Current Medical Imaging Formerly Current Medical Imaging Reviews · doi:10.2174/1573405616666201217112521 · Cited by 14

Improving Performance of a Brain Tumor Detection on MRI Images Using DCGAN-Based Data Augmentation and Vision Transformer (ViT) Approach

Haque, M. M., Paul, S. K., Paul, R. R., Islam, N., Hasan, M. A. F. M. R., & Hamid, M. E. (2023) · Springer eBooks · doi:10.1007/978-3-031-43205-7_10 · Cited by 13

Enhanced brain tumor classification using convolutional neural networks and ensemble voting classifier for improved diagnostic accuracy

Velpula, V. K., Vadlamudi, J., Janapati, M., Kasaraneni, P. P., Kumar, Y. V. P., Reddy, C. P., & Mallipeddi, R. (2025) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2025.110124 · Cited by 13

Convolutional Block Attention Module and Parallel Branch Architectures for Cervical Cell Classification

Cömert, Z., Efil, F., & Türkoğlu, M. (2025) · International Journal of Imaging Systems and Technology · doi:10.1002/ima.70048 · Cited by 13

Ultrasound Medical Images Classification Based on Deep Learning Algorithms: A Review

Kareem, F. Q., & Abdulazeez, A. M. (2021) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.4621288 · Cited by 13

Automated Detection and Classification of Meningioma Tumor from MR Images Using Sea Lion Optimization and Deep Learning Models

Sukumaran, A., & Abraham, A. (2021) · Axioms · doi:10.3390/axioms11010015 · Cited by 13

Ultrasound Medical Images Classification Based on Deep Learning Algorithms: A Review

admin, A., & Abdulazeez, A. M. (2021) · Fusion Practice and Applications · doi:10.54216/fpa.030102 · Cited by 13

Review on Deep Learning Methodologies in Medical Image Restoration and Segmentation

Christinal, H. A., Hephzibah, R., Kowsalya, G., Jayanthi, R., & Chandy, D. A. (2022) · Current Medical Imaging Formerly Current Medical Imaging Reviews · doi:10.2174/1573405618666220407112825 · Cited by 13

Diagnosis of Glioma, Menigioma and Pituitary brain tumor using MRI images recognition by Deep learning in Python

Mokri, S. M. G., Valadbeygi, N., & Grigoryeva, V. N. (2024) · EAI endorsed transactions on intelligent systems and machine learning applications. · doi:10.4108/eetismla.5410 · Cited by 12

A Deep Learning Architecture for Meningioma Brain Tumor Detection and Segmentation

Anita, J. N., & Kumaran, S. (2022) · Journal of Cancer Prevention · doi:10.15430/jcp.2022.27.3.192 · Cited by 12

Brain Tumor Classification using Fine-Tuning based Deep Transfer Learning and Support Vector Machine

Karim, P. J., Mahmood, S. R., & Şah, M. (2023) · International Journal of Computing and Digital Systems · doi:10.12785/ijcds/130108 · Cited by 12

A Novel Hybrid Deep Learning Framework for Detection and Categorization of Brain Tumor from Magnetic Resonance Images

Algani, Y. M. A., Rao, B. N., Kaur, C., Ashreetha, B., Sagar, K. V. D., & El–Ebiary, Y. A. B. (2023) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2023.0140261 · Cited by 12

CPRO: Competitive Poor and Rich Optimizer-Enabled Deep Learning Model and Holoentropy Weighted-Power K-Means Clustering for Brain Tumor Classification Using MRI

Agalya, V., Kandasamy, M., Venugopal, E., & Maram, B. (2022) · International Journal of Pattern Recognition and Artificial Intelligence · doi:10.1142/s0218001422520085 · Cited by 11

Enhancing Brain Tumor Detection on MRI Images Using an Innovative VGG-19 Model-Based Approach

Şener, A., & Ergen, B. (2023) · Sakarya University Journal of Science · doi:10.16984/saufenbilder.1302803 · Cited by 11

MEHW‐SVM multi‐kernel approach for improved brain tumour classification

Dheepak, G., Christaline, J. A., & Vaishali, D. (2023) · IET Image Processing · doi:10.1049/ipr2.12990 · Cited by 11

Automated Multimodal Brain Tumor Segmentation and Localization in MRI Images Using Hybrid Res2-UNeXt

Nehru, V., & Prabhu, V. (2024) · Journal of Electrical Engineering and Technology · doi:10.1007/s42835-023-01779-3 · Cited by 11

Brain MRI detection and classification: Harnessing convolutional neural networks and multi-level thresholding

Reddy, K. R., Rajesh, K. N. V. P. S., Dhuli, R., Polinati, S., Sonti, K., Tadeusiewicz, R., & Pławiak, P. (2024) · PLoS ONE · doi:10.1371/journal.pone.0306492 · Cited by 11

CNN based Deep Learning Approach for Brain Tumor Detection in MRI Images

Garg, A., Chauhan, A., Sahgal, A., & Shambharkar, P. G. (2023) · International Conference on Applied Artificial Intelligence and Computing (ICAAIC) · doi:10.1109/icaaic56838.2023.10140895 · Cited by 10

Transformative Advances in AI for Precise Cancer Detection: A Comprehensive Review of Non-Invasive Techniques

Rai, H. M., Yoo, J., & Dashkevych, S. (2025) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-024-10219-y · Cited by 9

A Survey on Various Machine Learning Techniques for an Efficient Brain Tumor Detection from MRI Images

Sanjay, V., & Swarnalatha, P. (2022) · International Journal of Electrical and Electronics Research · doi:10.37391/ijeer.100222 · Cited by 9

Deep learning architectures for Brain Tumor detection: A Survey

Divya, K. S., & Manish, T. I. (2023) · Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA) · doi:10.1109/accthpa57160.2023.10083385 · Cited by 9

Diagnosis of Medical Images Using Fuzzy Convolutional Neural Networks

Mahdi, H. A., Shujaa, M. I., & Zghair, E. M. (2023) · Mathematical Modelling and Engineering Problems · doi:10.18280/mmep.100428 · Cited by 9

A Novel Inherited Modeling Structure of Automatic Brain Tumor Segmentation from MRI

Asiri, A. A. M., Ali, T. M., Shaf, A., Aamir, M., Shoaib, M. A., Irfan, M., Alshamrani, H. A., Alqahtani, F. F., & Alshehri, O. M. (2022) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2022.030923 · Cited by 9

An integrated approach for breast cancer classification

Pandey, A., & Kumar, A. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-14782-7 · Cited by 9

Dynamic selectout and voting-based federated learning for enhanced medical image analysis

Iqbal, S., Qureshi, A. N., Alhussein, M. A., Aurangzeb, K., Mahmood, A., & Azzuhri, S. R. (2024) · Machine Learning Science and Technology · doi:10.1088/2632-2153/ada0a6 · Cited by 8

Ensembled EfficientNetB3 architecture for multi-class classification of tumours in MRI images

Dudeja, T., Dubey, S. K., & Bhatt, A. K. (2023) · Intelligent Decision Technologies · doi:10.3233/idt-220150 · Cited by 8

DeepMaizeNet: A novel hybrid approach based on CBAM for implementing the doubled haploid technique

Ayaz, I., Kutlu, F., & Cömert, Z. (2023) · Agronomy Journal · doi:10.1002/agj2.21396 · Cited by 8

Brain Tumor Classification using MR Images and Transfer Learning

Gupta, M., Shirisha, G., Chandana, A. M., & Ankitha, B. (2023) · International Conference on Edge Computing and Applications (ICECAA) · doi:10.1109/icecaa58104.2023.10212167 · Cited by 8

Brain Tumor Detection by using ResNet-50 and Image Processing Tools

Rathore, S., Rana, T., Mittal, U., Gupta, T., Malik, N., & S, M. S. A. (2023) · International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) · doi:10.1109/icacite57410.2023.10183081 · Cited by 7

EDLNet: ensemble deep learning network model for automatic brain tumor classification and segmentation

Vinta, S. R., Chintalapati, P. V., Babu, G. R., RajyaLakshmi, T., & Kumar, G. S. C. (2024) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2024.2311343 · Cited by 7

Automated Brain Tumor Classification and Grading Using Multi-scale Graph Neural Network with Spatio-Temporal Transformer Attention Through MRI Scans

Srivastava, S., Jain, P., Pandey, S. K., Dubey, G., & Das, N. N. (2025) · Interdisciplinary Sciences Computational Life Sciences · doi:10.1007/s12539-025-00718-2 · Cited by 7

Lightweight convolutional neural networks using nonlinear Lévy chaotic moth flame optimisation for brain tumour classification via efficient hyperparameter tuning

Dehkordi, A. A., Neshat, M., Khosravian, A., Thilakaratne, M., Sadiq, A. S., & Mirjalili, S. (2025) · Scientific Reports · doi:10.1038/s41598-025-02890-3 · Cited by 8

IV3TM: Inception V3 enabled bidirectional long short-term memory network for brain tumor classification

Alhassan, A. M., & Altmami, N. I. (2025) · PLoS ONE · doi:10.1371/journal.pone.0335397 · Cited by 7

Identification of Brain Tumor Images Using a Novel Machine Learning Model

Mahesha, Y. (2023) · Lecture notes in networks and systems · doi:10.1007/978-981-99-5166-6_30 · Cited by 7

Vulture-Based AdaBoost-Feedforward Neural Frame Work for COVID-19 Prediction and Severity Analysis System

Mary, S. R., Kumar, V., Venkatesan, K., Kumar, R. S., Jagini, N. P., & Srinivas, A. (2022) · Interdisciplinary Sciences Computational Life Sciences · doi:10.1007/s12539-022-00505-3 · Cited by 7

Detection of brain tumors from MR images using fuzzy thresholding and texture feature descriptor

Reddy, K. R., & Dhuli, R. (2023) · The Journal of Supercomputing · doi:10.1007/s11227-022-05033-x · Cited by 7

An augmented customized deep learning approach for brain tumour identification

Madhavan, M. V., Khamparia, A., & Pande, S. D. (2023) · The Imaging Science Journal · doi:10.1080/13682199.2023.2182382 · Cited by 7

Advances in the Use of Deep Learning for the Analysis of Magnetic Resonance Image in Neuro-Oncology

Pitarch, C., Ungan, G., Julià‐Sapé, M., & Vellido, A. (2024) · Cancers · doi:10.3390/cancers16020300 · Cited by 9

SADO-Net: A spatial adaptive dart optimized network model for an automated brain tumor diagnosis using MRIs

Dutta, A. K., Bokhari, Y., Alghayadh, F. Y., Alsubai, S., alhalabi, H. R. S., umer, M., & Sait, A. R. W. (2024) · Alexandria Engineering Journal · doi:10.1016/j.aej.2024.09.102 · Cited by 6

Hybrid Mobile-Spinalnet with feature extraction for brain tumor detection using MRI images

Vadivu, P. B., Prabhakar, T., Mandala, J., & Sekhar, K. V. C. (2025) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2025.108571 · Cited by 6

Hybrid Deep Learning for Brain Tumor Detection: Combining DenseNet and Custom CNN for Enhanced Accuracy

Swaminathan, A. D., Begum, A., Ramamoorthy, K., Nadarajan, R. N., Krishnamoorthy, S. V., Balachandran, P. K., & Kannan, S. (2025) · Biomedical Engineering and Computational Biology · doi:10.1177/11795972251395954 · Cited by 6

Advancements and emerging trends in brain tumor classification using MRI: a systematic review

Dixit, A., & Thakur, M. K. (2023) · Network Modeling Analysis in Health Informatics and Bioinformatics · doi:10.1007/s13721-023-00428-z · Cited by 6

Brain Tumor Detection using Machine Learning

Castelino, V. L., Vishnu, M., Shetty, K. S., Jain, P., Kamath, V. R., & Thanthri, V. (2024) · International Conference on Data Science and Information System (ICDSIS) · doi:10.1109/icdsis61070.2024.10594516 · Cited by 6

Multi‐class brain tumor classification system in MRI images using cascades neural network

Jayachandran, A., & Anisha, N. (2024) · Computational Intelligence · doi:10.1111/coin.12687 · Cited by 6

Advanced Hybrid Brain Tumor Segmentation in MRI: Elephant Herding Optimization Combined with Entropy-Guided Fuzzy Clustering

Karun, B., Thiyagarajan, A., Rajasekaran, M. P., Jeyaprakash, N., Ramaraj, K., & Makreri, R. (2024) · Mathematical and Computational Applications · doi:10.3390/mca30010001 · Cited by 6

Fine-Tuned EfficientNetB3 for Enhanced Brain Tumor Detection

Nasra, P., & Gupta, S. (2024) · International Conference on Data Intelligence and Cognitive Informatics (ICDICI) · doi:10.1109/icdici62993.2024.10810882 · Cited by 6

COVID-19 Diagnosis with Deep Learning

Reis, H. Ç. (2021) · Ingeniería e Investigación · doi:10.15446/ing.investig.v42n1.88825 · Cited by 7

An improved GABOR wavelet transform and rough k-means clustering algorithm for MRI BRAIN tumor image segmentation

Rao, B. C., Raju, K., Babu, G. R., & Pittala, C. S. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-14485-z · Cited by 6

Açıklanabilir Evrişimsel Sinir Ağları ile Beyin Tümörü Tespiti

Orman, A., Köse, U., & Yi̇ği̇t, T. (2021) · El-Cezeri Fen ve Mühendislik Dergisi · doi:10.31202/ecjse.924446 · Cited by 6

Brain tumor diagnosis techniques key achievements, lessons learned, and a new CNN architecture

Salama, G. M., Abd-Ellah, M. K., Hussein, A. I., Bayoumi, E. S., Ashraf, S., & Elwan, M. (2025) · The Egyptian Journal of Radiology and Nuclear Medicine · doi:10.1186/s43055-025-01567-1 · Cited by 5

Explainable Hybrid Deep Learning Framework Integrating MobileNetV2, EfficientNetV2B0, and KNN for MRI-Based Brain Tumor Classification

Adamu, M. J., Li, Q., Nyatega, C. O., Fahad, M., Younis, A., Jabire, A. H., Zakariyya, R. S., & Kawuwa, H. B. (2026) · Cellular and Molecular Neurobiology · doi:10.1007/s10571-025-01660-z · Cited by 5

Addressing challenges in accurate brain tumor classification in MRI: a transfer learning approach with EfficientNetB3 and comprehensive model evaluation

Das, S., & Goswami, R. S. (2024) · Multimedia Tools and Applications · doi:10.1007/s11042-024-20366-w · Cited by 5

Integrating YOLOV8 and Grad-CAM++ for Enhanced Brain Tumor Detection and Interpretation

Parvathavarthini, S., Danushree, V. S., Krupa, N. S., & Sowndharya, R. (2025) · International Conference on Inventive Computation Technologies (ICICT) · doi:10.1109/icict64420.2025.11004921 · Cited by 5

Deep transfer learning based feature fusion model with Bonobo optimization algorithm for enhanced brain tumor segmentation and classification through biomedical imaging

Gurunathan, P., Srinivasan, P. S., & Ravimaran, S. (2025) · Scientific Reports · doi:10.1038/s41598-025-12973-w · Cited by 5

A Transfer Learning-Based Model for Brain Tumor Detection in MRI Images

Hencya, F. R., Mandala, S., Tang, T. B., & Zahid, M. S. M. (2023) · Jurnal Nasional Teknik Elektro · doi:10.25077/jnte.v12n2.1123.2023 · Cited by 5

Fine-Tuning based Deep Transfer Learning System used to Identify the Stage of Brain Tumour from MR-Images

Pilli, N., Nikilish, P., & Shankar, R. S. (2023) · International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) · doi:10.1109/icaiss58487.2023.10250555 · Cited by 5

Brain tumor recognition from multimodal magnetic resonance images using wavelet texture features and optimized artificial neural network

Yadav, A. K., & Yadav, V. (2024) · Multimedia Tools and Applications · doi:10.1007/s11042-024-18489-1 · Cited by 5

Brain Tumor Detection Using Convolutional Neural Networks (CNNs)

Aryal, S., Sharma, S., Sedai, S., Aryal, P., & Mansur, J. (2023) · Kathford Journal of Engineering and Management · doi:10.3126/kjem.v3i1.62888 · Cited by 5

BRAIN TUMOR SEGMENTATION AND CLASSIFICATION USING OPTIMIZED U-NET

Shiny, K. V. (2023) · Journal of Mechanics in Medicine and Biology · doi:10.1142/s0219519423500501 · Cited by 5

Congruence of deep learning in biomedical engineering

Behura, A. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-823014-5.00003-x · Cited by 5

Extreme Learning Bat Algorithm in Brain Tumor Classification

Sreekanth, G. R., Alrasheedi, A. F., Venkatachalam, K., Abouhawwash, M., & Askar, S. S. (2022) · Intelligent Automation & Soft Computing · doi:10.32604/iasc.2022.024538 · Cited by 5

Deep Learning Based Brain Tumor Diagnosis with Pre-Trained and Self-Attention Based Models Using MRI Scans: A Systematic Literature Review

Goyal, B., Hans, R., Sharma, S. K., & Singh, H. (2026) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-026-10531-9 · Cited by 4

Deep learning model for brain tumour detection

Yadav, A., Kumar, R., & Gupta, M. (2024) · AIP conference proceedings · doi:10.1063/5.0216147 · Cited by 4

3D densely connected CNN with multi-scale receptive fields and hybrid loss for brain tumor segmentation

Adib, F. Z., Amirmazlaghani, M., & Rahmati, M. (2025) · Discover Artificial Intelligence · doi:10.1007/s44163-025-00279-9 · Cited by 4

Brain Tumor Analysis Using Deep Neural Network

Khan, I., Ahsan, K., Hasan, M. A., & Sattar, A. (2021) · International Conference on Intelligent Computing and Control Systems (ICICCS) · doi:10.1109/iciccs51141.2021.9432235 · Cited by 4

Brain Tumors Detection on MRI Images with K-means Clustering and Residual Networks

Nguyễn, H. T., Luong, H. H., Kien, T. H. N., Phan, N. T. L., Dang, T. M., Duong, T. T., Nguyen, T. D., & Dinh, T. C. (2022) · Communications in computer and information science · doi:10.1007/978-3-031-16210-7_26 · Cited by 4

Detection of Brain Cancer using Machine Learning Techniques a Review

Meghana, G., Rudrahithlu, S. K., & Shilpa, K. C. (2022) · International Journal of Computer Science and Engineering · doi:10.14445/23488387/ijcse-v9i9p102 · Cited by 4

Chest X-Ray Image Analysis with ResNet50, SMOTE and SafeSMOTE

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