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

COVID-19 detection using deep learning models to exploit Social Mimic Optimization and structured chest X-ray images using fuzzy color and stacking approaches

Toğaçar, M., Ergen, B., & Cömert, Z. (2020) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2020.103805 · Cited by 574

Application of deep learning techniques for detection of COVID-19 cases using chest X-ray images: A comprehensive study

Nayak, S. R., Nayak, D. R., Sinha, U., Arora, V., & Pachori, R. B. (2020) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2020.102365 · Cited by 401

A Novel Medical Diagnosis model for COVID-19 infection detection based on Deep Features and Bayesian Optimization

Nour, M., Cömert, Z., & Polat, K. (2020) · Applied Soft Computing · doi:10.1016/j.asoc.2020.106580 · Cited by 316

Multi-Modal Brain Tumor Detection Using Deep Neural Network and Multiclass SVM

Maqsood, S., Damaševičius, R., & Maskeliūnas, R. (2022) · Medicina · doi:10.3390/medicina58081090 · Cited by 313

Machine Learning and Deep Learning Approaches for Brain Disease Diagnosis: Principles and Recent Advances

Khan, P., Kader, M. F., Islam, S. M. R., Rahman, A. B., Kamal, M. S., Toha, M. U., & Kwak, K. S. (2021) · IEEE Access · doi:10.1109/access.2021.3062484 · Cited by 314

Role of deep learning in brain tumor detection and classification (2015 to 2020): A review

Nazir, M., Shakil, S., & Khurshid, K. (2021) · Computerized Medical Imaging and Graphics · doi:10.1016/j.compmedimag.2021.101940 · Cited by 293

Improving Effectiveness of Different Deep Transfer Learning-Based Models for Detecting Brain Tumors From MR Images

Asif, S., Yi, W., Ain, Q. U., Hou, J., Tao, Y., & Si, J. (2022) · IEEE Access · doi:10.1109/access.2022.3153306 · Cited by 221

MRI brain tumor detection and classification using parallel deep convolutional neural networks

Rahman, T., & Islam, M. S. (2023) · Measurement Sensors · doi:10.1016/j.measen.2023.100694 · Cited by 216

A classification of MRI brain tumor based on two stage feature level ensemble of deep CNN models

Aurna, N. F., Yousuf, M. A., Taher, K. A., Azad, A., & Moni, M. A. (2022) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2022.105539 · Cited by 212

Automated Brain Tumor Segmentation and Classification in MRI Using YOLO-Based Deep Learning

Almufareh, M. F., Imran, M., Khan, A., Humayun, M., & Asim, M. F. (2024) · IEEE Access · doi:10.1109/access.2024.3359418 · Cited by 218

Early Diagnosis of Brain Tumour MRI Images Using Hybrid Techniques between Deep and Machine Learning

Senan, E. M., Jadhav, M. E., Rassem, T. H., Aljaloud, A. S., Mohammed, B. A., & Al-Mekhlafi, Z. G. (2022) · Computational and Mathematical Methods in Medicine · doi:10.1155/2022/8330833 · Cited by 184

Differential Deep Convolutional Neural Network Model for Brain Tumor Classification

Kader, I. A. E., Xu, G., Zhang, S., Saminu, S., Javaid, I., & Ahmad, I. S. (2021) · Brain Sciences · doi:10.3390/brainsci11030352 · Cited by 198

An enhanced deep learning method for multi-class brain tumor classification using deep transfer learning

Asif, S., Zhao, M., Tang, F., & Zhu, Y. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-14828-w · Cited by 174

Transfer Learning Using Convolutional Neural Network Architectures for Brain Tumor Classification from MRI Images

Chelghoum, R., Ikhlef, A., Hameurlaine, A., & Jacquir, S. (2020) · IFIP advances in information and communication technology · doi:10.1007/978-3-030-49161-1_17 · Cited by 164

Brain Tumor Detection and Multi-Grade Segmentation Through Hybrid Caps-VGGNet Model

Jabbar, A., Naseem, S., Mahmood, T., Saba, T., Alamri, F. S., & Rehman, A. U. (2023) · IEEE Access · doi:10.1109/access.2023.3289224 · Cited by 150

Intelligent skin cancer detection applying autoencoder, MobileNetV2 and spiking neural networks

Toğaçar, M., Cömert, Z., & Ergen, B. (2021) · Chaos Solitons & Fractals · doi:10.1016/j.chaos.2021.110714 · Cited by 148

On the Performance of Deep Transfer Learning Networks for Brain Tumor Detection Using MR Images

Ahmad, S., & Choudhury, P. K. (2022) · IEEE Access · doi:10.1109/access.2022.3179376 · Cited by 163

Waste classification using AutoEncoder network with integrated feature selection method in convolutional neural network models

Toğaçar, M., Ergen, B., & Cömert, Z. (2019) · Measurement · doi:10.1016/j.measurement.2019.107459 · Cited by 128

Computer-Aided Brain Tumor Diagnosis: Performance Evaluation of Deep Learner CNN Using Augmented Brain MRI

Naseer, A., Yasir, T., Azhar, A., Shakeel, T., & Zafar, K. (2021) · International Journal of Biomedical Imaging · doi:10.1155/2021/5513500 · Cited by 119

A Novel and Effective Brain Tumor Classification Model Using Deep Feature Fusion and Famous Machine Learning Classifiers

Kibriya, H., Amin, R., Alshehri, A. H., Masood, M., Alshamrani, S. S., & Alshehri, A. (2022) · Computational Intelligence and Neuroscience · doi:10.1155/2022/7897669 · Cited by 122

An MRI-based deep learning approach for efficient classification of brain tumors

Haq, E. U., Jianjun, H., Li, K., Haq, H. U., & Zhang, T. (2021) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-021-03535-9 · Cited by 112

A Comprehensive Analysis of Recent Deep and Federated-Learning-Based Methodologies for Brain Tumor Diagnosis

Naeem, A., Anees, T., Naqvi, R. A., & Loh, W.-K. (2022) · Journal of Personalized Medicine · doi:10.3390/jpm12020275 · Cited by 103

A comprehensive survey on convolutional neural network in medical image analysis

Yao, X., Wang, X., Wang, S., & Zhang, Y. (2020) · Multimedia Tools and Applications · doi:10.1007/s11042-020-09634-7 · Cited by 101

2D MRI image analysis and brain tumor detection using deep learning CNN model LeU-Net

Rai, H. M., & Chatterjee, K. (2021) · Multimedia Tools and Applications · doi:10.1007/s11042-021-11504-9 · Cited by 104

A modified reptile search algorithm for global optimization and image segmentation: Case study brain MRI images

Emam, M. M., Houssein, E. H., & Ghoniem, R. M. (2022) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2022.106404 · Cited by 100

An Efficient Multi-Scale Convolutional Neural Network Based Multi-Class Brain MRI Classification for SaMD

Yazdan, S. A., Ahmad, R., Iqbal, N., Rizwan, A., Khan, A. N., & Kim, D. (2022) · Tomography · doi:10.3390/tomography8040161 · Cited by 94

Classification of flower species by using features extracted from the intersection of feature selection methods in convolutional neural network models

Toğaçar, M., Ergen, B., & Cömert, Z. (2020) · Measurement · doi:10.1016/j.measurement.2020.107703 · Cited by 89

An Efficient Approach for the Detection of Brain Tumor Using Fuzzy Logic and U-NET CNN Classification

Maqsood, S., Damaševičius, R., & Shah, F. M. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-86976-2_8 · Cited by 89

Automated Detection of Brain Tumor through Magnetic Resonance Images Using Convolutional Neural Network

Gull, S., Akbar, S., & Khan, H. U. (2021) · BioMed Research International · doi:10.1155/2021/3365043 · Cited by 92

Brain Tumor Detection and Classification on MR Images by a Deep Wavelet Auto-Encoder Model

Kader, I. A. E., Xu, G., Zhang, S., Saminu, S., Javaid, I., Ahmad, I. S., & Kamhi, S. (2021) · Diagnostics · doi:10.3390/diagnostics11091589 · Cited by 100

Optimized deep learning architecture for brain tumor classification using improved Hunger Games Search Algorithm

Emam, M. M., Samee, N. M. A., Jamjoom, M. M., & Houssein, E. H. (2023) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2023.106966 · Cited by 90

TumorDetNet: A unified deep learning model for brain tumor detection and classification

Ullah, N., Javed, A., Alhazmi, A. H., Hasnain, S. M., Tahir, A., & Ashraf, R. (2023) · PLoS ONE · doi:10.1371/journal.pone.0291200 · Cited by 81

Transfer learning architectures with fine-tuning for brain tumor classification using magnetic resonance imaging

Islam, M. M., Barua, P., Rahman, M., Ahammed, T., Akter, L., & Uddin, J. (2023) · Healthcare Analytics · doi:10.1016/j.health.2023.100270 · Cited by 78

Multiclass classification of brain tumors using a novel CNN architecture

Kibriya, H., Masood, M., Nawaz, M., & Nazir, T. (2022) · Multimedia Tools and Applications · doi:10.1007/s11042-022-12977-y · Cited by 72

Brain Tumor Classification and Detection Based DL Models: A Systematic Review

Neamah, K., Mohamed, F., Adnan, M. M., Saba, T., Bahaj, S. A., Kadhim, K. A., & Rehman, A. U. (2023) · IEEE Access · doi:10.1109/access.2023.3347545 · Cited by 74

Tumor type detection in brain MR images of the deep model developed using hypercolumn technique, attention modules, and residual blocks

Toğaçar, M., Ergen, B., & Cömert, Z. (2020) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-020-02290-x · Cited by 69

A Transfer Learning-Based Approach for Brain Tumor Classification

Bibi, N., Wahid, F., Ma, Y., Ali, S., Abbasi, I. A., Alkhayyat, A. H., & Khyber (2024) · IEEE Access · doi:10.1109/access.2024.3425469 · Cited by 68

A new brain tumor diagnostic model: Selection of textural feature extraction algorithms and convolution neural network features with optimization algorithms

Başaran, E. (2022) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2022.105857 · Cited by 67

Improving brain tumor classification with combined convolutional neural networks and transfer learning

İncir, R., & Bozkurt, F. (2024) · Knowledge-Based Systems · doi:10.1016/j.knosys.2024.111981 · Cited by 69

Computer-Aided Early Melanoma Brain-Tumor Detection Using Deep-Learning Approach

Asad, R., Rehman, S. U., Imran, A., Li, J., Almuhaimeed, A., & Alzahrani, A. (2023) · Biomedicines · doi:10.3390/biomedicines11010184 · Cited by 75

Detection of brain abnormality by a novel Lu-Net deep neural CNN model from MR images

Rai, H. M., & Chatterjee, K. (2020) · Machine Learning with Applications · doi:10.1016/j.mlwa.2020.100004 · Cited by 64

Machine Learning Empowered Brain Tumor Segmentation and Grading Model for Lifetime Prediction

Renugadevi, M., Narasimhan, K., Ravikumar, C. V., Anbazhagan, R., Pau, G., Ramkumar, K., Abbas, M. A. E., Raju, N., Sathish, K., & Prabu, S. (2023) · IEEE Access · doi:10.1109/access.2023.3326841 · Cited by 63

A Sequential Machine Learning-cum-Attention Mechanism for Effective Segmentation of Brain Tumor

Ali, T. M., Nawaz, A., Rehman, A. U., Ahmad, R. Z., Javed, A. R., Gadekallu, T. R., Chen, C., & Wu, C.-M. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.873268 · Cited by 60

DCNNBT: A NOVEL DEEP CONVOLUTION NEURAL NETWORK-BASED BRAIN TUMOR CLASSIFICATION MODEL

Haq, M. A., Khan, I., Ahmed, A. U., Eldin, S. M., Alshehri, A., & Ghamry, N. A. (2023) · Fractals · doi:10.1142/s0218348x23401023 · Cited by 60

VGG16 Feature Extractor with Extreme Gradient Boost Classifier for Pancreas Cancer Prediction

Bakasa, W., & Viriri, S. (2023) · Journal of Imaging · doi:10.3390/jimaging9070138 · Cited by 69

Ensemble Learning Driven Computer-Aided Diagnosis Model for Brain Tumor Classification on Magnetic Resonance Imaging

Vaiyapuri, T., Mahalingam, J., Ahmad, S., Abdeljaber, H. A. M., Yang, E., & Jeong, S. (2023) · IEEE Access · doi:10.1109/access.2023.3306961 · Cited by 60

Brain Tumor Detection and Classification Using an Optimized Convolutional Neural Network

Aamir, M., Namoun, A., Munir, S., Aljohani, N. F., Alanazi, M. H., Alsahafi, Y. A., & Alotibi, F. (2024) · Diagnostics · doi:10.3390/diagnostics14161714 · Cited by 60

Optimized deep learning model for comprehensive medical image analysis across multiple modalities

Khan, S. U. R., Asif, S., Zhao, M., Zou, W., Li, Y., & Li, X. (2024) · Neurocomputing · doi:10.1016/j.neucom.2024.129182 · Cited by 59

Deep Learning Techniques for the Classification of Brain Tumor: A Comprehensive Survey

Younis, A., Li, Q., Khalid, M., Clemence, B., & Adamu, M. J. (2023) · IEEE Access · doi:10.1109/access.2023.3317796 · Cited by 59

Brain Tumor Detection and Prediction in MRI Images Utilizing a Fine-Tuned Transfer Learning Model Integrated Within Deep Learning Frameworks

Rastogi, D., Johri, P., Donelli, M., Kumar, L., Bindewari, S., Raghav, A., & Khatri, S. K. (2025) · Life · doi:10.3390/life15030327 · Cited by 57

AI in MRI brain tumor diagnosis: A systematic review of machine learning and deep learning advances (2010–2025)

Satushe, V., Vyas, V., Metkar, S. P., & Singh, D. P. (2025) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/j.chemolab.2025.105414 · Cited by 56

C+EffxNet: A novel hybrid approach for COVID-19 diagnosis on CT images based on CBAM and EfficientNet

Canayaz, M. (2021) · Chaos Solitons & Fractals · doi:10.1016/j.chaos.2021.111310 · Cited by 55

A Survey of Computer-Aided Tumor Diagnosis Based on Convolutional Neural Network

Yan, Y., Yao, X., Wang, S., & Zhang, Y. (2021) · Biology · doi:10.3390/biology10111084 · Cited by 53

Computationally optimized brain tumor classification using attention based GoogLeNet-style CNN

Subba, A. B., & Sunaniya, A. K. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.125443 · Cited by 51

A lightweight multi-path convolutional neural network architecture using optimal features selection for multiclass classification of brain tumor using magnetic resonance images

Batool, A., & Byun, Y.-C. (2025) · Results in Engineering · doi:10.1016/j.rineng.2025.104327 · Cited by 57

Deep Learning-based Transfer Learning Model in Diagnosis of Diseases with Brain Magnetic Resonance Imaging

Suganthe, R. C., Muthusamy, G., Sevalaiappan, L. R., & Senthilkumaran, N. (2022) · Acta Polytechnica Hungarica · doi:10.12700/aph.19.5.2022.5.7 · Cited by 48

Otitis media detection using tympanic membrane images with a novel multi-class machine learning algorithm

Alhudhaif, A., Cömert, Z., & Polat, K. (2021) · PeerJ Computer Science · doi:10.7717/peerj-cs.405 · Cited by 45

An improved deep convolutional neural network by using hybrid optimization algorithms to detect and classify brain tumor using augmented MRI images

Qader, S. M., Hassan, B. A., & Rashid, T. A. (2022) · Multimedia Tools and Applications · doi:10.1007/s11042-022-13260-w · Cited by 47

A comprehensive analysis of recent advancements in cancer detection using machine learning and deep learning models for improved diagnostics

Rai, H. M., & Yoo, J. (2023) · Journal of Cancer Research and Clinical Oncology · doi:10.1007/s00432-023-05216-w · Cited by 50

MRI-Based Brain Tumor Classification Using a Dilated Parallel Deep Convolutional Neural Network

Rahman, T., Islam, M. S., & Uddin, J. (2024) · Digital · doi:10.3390/digital4030027 · Cited by 43

Automated Brain Tumor Identification in Biomedical Radiology Images: A Multi-Model Ensemble Deep Learning Approach

Natha, S. A. S., Laila, U., Gashim, I. A., Mahboob, K., Saeed, M. N., & Noaman, K. M. (2024) · Applied Sciences · doi:10.3390/app14052210 · Cited by 45

Early detection of brain tumors: Harnessing the power of GRU networks and hybrid dwarf mongoose optimization algorithm

Yuxia, Y., Chaoluomeng, & Razmjooy, N. (2024) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2024.106093 · Cited by 39

Lead-cnn: lightweight enhanced dimension reduction convolutional neural network for brain tumor classification

Khan, S. U. R., Asif, S., Bilal, O., & Rehman, H. U. (2025) · International Journal of Machine Learning and Cybernetics · doi:10.1007/s13042-025-02637-6 · Cited by 39

An approach for brain tumor detection using optimal feature selection and optimized deep belief network

Kumar, T. S., Arun, C., & Ezhumalai, P. (2021) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2021.103440 · Cited by 39

Graph attention autoencoder inspired CNN based brain tumor classification using MRI

Mishra, L., & Verma, S. (2022) · Neurocomputing · doi:10.1016/j.neucom.2022.06.107 · Cited by 37

Machine Learning-Based Models for Magnetic Resonance Imaging (MRI)-Based Brain Tumor Classification

Asiri, A. A. M., Khan, B. A., Muhammad, F., Rahman, S. U., Alshamrani, H. A., Alshamrani, K. A., Irfan, M., & Alqhtani, F. F. (2022) · Intelligent Automation & Soft Computing · doi:10.32604/iasc.2023.032426 · Cited by 37

A Novel Lightweight CNN Architecture for the Diagnosis of Brain Tumors Using MR Images

Reddy, K. R., & Dhuli, R. (2023) · Diagnostics · doi:10.3390/diagnostics13020312 · Cited by 41

Comprehensive Review on MRI-Based Brain Tumor Segmentation: A Comparative Study from 2017 Onwards

Verma, A., Shivhare, S. N., Singh, S. P., Kumar, N., & Nayyar, A. (2024) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-024-10128-0 · Cited by 35

Prediction Model of Aryl Hydrocarbon Receptor Activation by a Novel QSAR Approach, DeepSnap–Deep Learning

Matsuzaka, Y., Hosaka, T., Ogaito, A., Yoshinari, K., & Uesawa, Y. (2020) · Molecules · doi:10.3390/molecules25061317 · Cited by 35

Advancements in brain tumor analysis: a comprehensive review of machine learning, hybrid deep learning, and transfer learning approaches for MRI-based classification and segmentation

Das, S., & Goswami, R. S. (2024) · Multimedia Tools and Applications · doi:10.1007/s11042-024-20203-0 · Cited by 34

Brain MRI analysis using deep neural network for medical of internet things applications

Masood, M., Maham, R., Javed, A., Tariq, U., Khan, M. A., & Kadry, S. (2022) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2022.108386 · Cited by 34

Explainable AI and vision transformers for detection and classification of brain tumor: a comprehensive survey

Hosny, K. M., & Mohammed, M. (2025) · Artificial Intelligence Review · doi:10.1007/s10462-025-11221-x · Cited by 40

Computer-aided diagnosis for multi-class classification of brain tumors using CNN features via transfer-learning

Yadav, A. C., Shah, K., Purohit, A., & Kolekar, M. H. (2025) · Multimedia Tools and Applications · doi:10.1007/s11042-025-20751-z · Cited by 30

AI‐Enhanced Detection of Clinically Relevant Structural and Functional Anomalies in MRI : Traversing the Landscape of Conventional to Explainable Approaches

Khosravi, P., Mohammadi, S., Zahiri, F., Khodarahmi, M., & Zahiri, J. (2024) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.29247 · Cited by 30

Application of artificial intelligence and radiomics in pituitary neuroendocrine and sellar tumors: a quantitative and qualitative synthesis

Koong, K., Preda, V. A., Jian, A., Liquet, B., & Ieva, A. D. (2021) · Neuroradiology · doi:10.1007/s00234-021-02845-1 · Cited by 27

Automatic Brain Tumor Detection and Classification Based on IoT and Machine Learning Techniques

Sundarasekar, R., & Appathurai, A. (2022) · Fluctuation and Noise Letters · doi:10.1142/s0219477522500304 · Cited by 29

Efficient and Accurate Brain Tumor Classification Using Hybrid MobileNetV2–Support Vector Machine for Magnetic Resonance Imaging Diagnostics in Neoplasms

Adamu, M. J., Kawuwa, H. B., Li, Q., Nyatega, C. O., Younis, A., Fahad, M., & Dauya, S. S. (2024) · Brain Sciences · doi:10.3390/brainsci14121178 · Cited by 37

Design, analysis and implementation of efficient deep learning frameworks for brain tumor classification

Verma, A., & Singh, V. P. (2022) · Multimedia Tools and Applications · doi:10.1007/s11042-022-13545-0 · Cited by 28

The Cluster Analysis and Feature Selection: Perspective of Machine Learning and Image Processing

Behura, A. (2021) · Wiley eBooks · doi:10.1002/9781119785620.ch10 · Cited by 30

LitefusionNet: Boosting the performance for medical image classification with an intelligent and lightweight feature fusion network

Asif, S., Ain, Q. U., Al-Sabri, R., & Abdullah, M. (2024) · Journal of Computational Science · doi:10.1016/j.jocs.2024.102324 · Cited by 25

Revolutionizing Brain Tumor Detection Using Explainable AI in MRI Images

Islam, M. A., Mridha, M. F., Safran, M., Alfarhood, S., & Kabir, M. M. (2025) · NMR in Biomedicine · doi:10.1002/nbm.70001 · Cited by 28

A review on cancer detection strategies with help of biomedical images using machine learning techniques

Kumaraswamy, E., Sharma, S., & Kumar, S. (2022) · AIP conference proceedings · doi:10.1063/5.0081936 · Cited by 24

Earlier Detection of Brain Tumor by Pre-Processing Based on Histogram Equalization with Neural Network

Ramamoorthy, M., Qamar, S., Manikandan, R., Jhanjhi, N. Z., Masud, M., & AlZain, M. A. (2022) · Healthcare · doi:10.3390/healthcare10071218 · Cited by 25

An integrated deep learning and supervised learning approach for early detection of brain tumor using magnetic resonance imaging

Lamba, K., Rani, S., Anand, M., & Maguluri, L. P. (2024) · Healthcare Analytics · doi:10.1016/j.health.2024.100336 · Cited by 23

Advancements in brain tumor identification: Integrating synthetic GANs with federated-CNNs in medical imaging analysis

Alalwan, N., Alwadain, A. S., Alzahrani, A. I., Al-Bayatti, A. H., Abozeid, A., & El-Aziz, R. M. A. (2024) · Alexandria Engineering Journal · doi:10.1016/j.aej.2024.06.080 · Cited by 23

The power of deep learning for intelligent tumor classification systems: A review

Chandni, Sachdeva, M., & Kushwaha, A. K. S. (2023) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2023.108586 · Cited by 24

StynMedGAN: Medical images augmentation using a new GAN model for improved diagnosis of diseases

Wali, A., Ahmad, M., Naseer, A., Tamoor, M., & Gilani, S. A. M. (2023) · Journal of Intelligent & Fuzzy Systems · doi:10.3233/jifs-223996 · Cited by 25

Classification of brain tumor types through MRIs using parallel CNNs and firefly optimization

Li, C., Zhang, F., Du, Y., & Li, H. (2024) · Scientific Reports · doi:10.1038/s41598-024-65714-w · Cited by 23

Precision meets generalization: Enhancing brain tumor classification via pretrained DenseNet with global average pooling and hyperparameter tuning

Aziz, N., Minallah, N., Frnda, J., Sher, M., Zeeshan, M., & Haroon, A. (2024) · PLoS ONE · doi:10.1371/journal.pone.0307825 · Cited by 22

Context aware machine learning techniques for brain tumor classification and detection – A review

Amjad, U., Raza, A., Fahad, M., Farid, D., Akhunzada, A., Abubakar, M., & Beenish, H. (2025) · Heliyon · doi:10.1016/j.heliyon.2025.e41835 · Cited by 24

Image-based state-of-the-art techniques for the identification and classification of brain diseases: a review

Haq, E. U., Huang, J., Li, K., Haq, H. U., & Zhan, T. (2020) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-020-02256-z · Cited by 22

Transfer Learning-Based Deep Feature Extraction Framework Using Fine-Tuned EfficientNet B7 for Multiclass Brain Tumor Classification

Ghosh, A., Soni, B., & Baruah, U. (2023) · Arabian Journal for Science and Engineering · doi:10.1007/s13369-023-08607-w · Cited by 27

Hybrid Parallel Fuzzy CNN Paradigm: Unmasking Intricacies for Accurate Brain MRI Insights

Iqbal, S., Qureshi, A. N., Aurangzeb, K., Alhussein, M. A., Wang, S., Anwar, M. S., & Khan, F. N. (2024) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2024.3372608 · Cited by 24

Early Tumor Diagnosis in Brain MR Images via Deep Convolutional Neural Network Model

Das, T. K., Roy, P. K., Uddin, M., Srinivasan, K., Chang, C., & Syed-Abdul, S. (2021) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2021.016698 · Cited by 22

Real-time brain tumour diagnoses using a novel lightweight deep learning model

Alnageeb, M. H. O., & Supriya, M. H. (2025) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2025.110242 · Cited by 21

A Two-Tier Framework Based on GoogLeNet and YOLOv3 Models for Tumor Detection in MRI

Ali, F., Khan, S. N., Abbas, A. W., Shah, B., Hussain, T., Song, D., EI-Sappagh, S., & Singh, J. (2022) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2022.024103 · Cited by 21

Improvement of Automatic Glioma Brain Tumor Detection Using Deep Convolutional Neural Networks

Altameem, A., Mallikarjuna, B., Saudagar, A. K. J., Sharma, M., & Poonia, R. C. (2022) · Journal of Computational Biology · doi:10.1089/cmb.2021.0280 · Cited by 21

Deep residual network based brain tumor segmentation and detection with MRI using improved invasive bat algorithm

Gupta, V. K., & Bibhu, V. (2022) · Multimedia Tools and Applications · doi:10.1007/s11042-022-13769-0 · Cited by 21

A framework for brain tumor detection based on segmentation and features fusion using MRI images

Mostafa, A. M., El-Meligy, M. A., Alkhayyal, M. A., Alnuaim, A. A., & Sharaf, M. A. F. (2023) · Brain Research · doi:10.1016/j.brainres.2023.148300 · Cited by 21

An optimized ensemble model with advanced feature selection for network intrusion detection

Ahmed, A., Asim, M., Ullah, I., Zain-Ul-Abidin, & Ateya, A. A. (2024) · PeerJ Computer Science · doi:10.7717/peerj-cs.2472 · Cited by 20

Classification of brain MRI using hyper column technique with convolutional neural network and feature selection method

Toğaçar, M., Cömert, Z., & Ergen, B. (2020) · Expert Systems with Applications · doi:10.1016/j.eswa.2020.113274 · Cited by 132

Tumor type detection in brain MR images of the deep model developed using hypercolumn technique, attention modules, and residual blocks

Toğaçar, M., Ergen, B., & Cömert, Z. (2020) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-020-02290-x · Cited by 69

A novel convolutional neural network‐based approach for brain tumor classification using magnetic resonance images

Çınar, N., Kaya, M., & Kaya, B. (2022) · International Journal of Imaging Systems and Technology · doi:10.1002/ima.22839 · Cited by 37

Detection of tumors on brain MRI images using the hybrid convolutional neural network architecture

Çınar, A., & Yıldırım, M. (2020) · Medical Hypotheses · doi:10.1016/j.mehy.2020.109684 · Cited by 434

Detection of Brain Tumor Using Novel Convolutional Neural Network with Magnetic Resonance Imaging

Devi, K., & Sharma, A. (2023) · International Conference on Image Information Processing (ICIIP) · doi:10.1109/iciip61524.2023.10537668 · Cited by 1