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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Automated Brain Tumor Segmentation Based on Multi-Planar Superpixel Level Features Extracted From 3D MR Images
Tamjid Imtiaz, Shahriar Rifat, Shaikh Anowarul Fattah, et al.
IEEE Access (2019) Vol. 8, pp. 25335-25349
Open Access | Times Cited: 39

Showing 1-25 of 39 citing articles:

Selecting critical features for data classification based on machine learning methods
Rung-Ching Chen, Christine Dewi, Su-Wen Huang, et al.
Journal Of Big Data (2020) Vol. 7, Iss. 1
Open Access | Times Cited: 689
Brain Image Segmentation in Recent Years: A Narrative Review
Ali Fawzi, Anusha Achuthan, Bahari Belaton
Brain Sciences (2021) Vol. 11, Iss. 8, pp. 1055-1055
Open Access | Times Cited: 51
A survey of methods for brain tumor segmentation-based MRI images
Yahya M.A. Mohammed, Said El Garouani, Ismail Jellouli
Journal of Computational Design and Engineering (2022) Vol. 10, Iss. 1, pp. 266-293
Open Access | Times Cited: 31
Automatic brain tumor segmentation from Multiparametric MRI based on cascaded 3D U-Net and 3D U-Net++
Pengyu Li, Wenhao Wu, Lanxiang Liu, et al.
Biomedical Signal Processing and Control (2022) Vol. 78, pp. 103979-103979
Closed Access | Times Cited: 27
Comprehensive Survey on Computational Techniques for Brain Tumor Detection: Past, Present and Future
Priyanka Datta, Rajesh Rohilla
Archives of Computational Methods in Engineering (2025)
Closed Access
A computation-efficient CNN system for high-quality brain tumor segmentation
Yanming Sun, Chunyan Wang
Biomedical Signal Processing and Control (2022) Vol. 74, pp. 103475-103475
Open Access | Times Cited: 23
Comprehensive Review on MRI-Based Brain Tumor Segmentation: A Comparative Study from 2017 Onwards
Amit Verma, Shiv Naresh Shivhare, Shailendra Pratap Singh, et al.
Archives of Computational Methods in Engineering (2024)
Closed Access | Times Cited: 4
A Fully Automatic Procedure for Brain Tumor Segmentation from Multi-Spectral MRI Records Using Ensemble Learning and Atlas-Based Data Enhancement
Ágnes Györfi, László Szilágyi, Levente Kovács
Applied Sciences (2021) Vol. 11, Iss. 2, pp. 564-564
Open Access | Times Cited: 24
Development of an enhanced U-Net model for brain tumor segmentation with optimized architecture
G. Mahesh Kumar, P. Eswaran
Biomedical Signal Processing and Control (2022) Vol. 81, pp. 104427-104427
Closed Access | Times Cited: 17
BTFCNN: Design of a brain tumor classification model using fused convolutional neural networks
Vikas Kushwaha, Priya Maidamwar
2022 10th International Conference on Emerging Trends in Engineering and Technology - Signal and Information Processing (ICETET-SIP-22) (2022)
Closed Access | Times Cited: 15
Automated brain tumor identification using magnetic resonance imaging: A systematic review and meta-analysis
Omar Kouli, A Hassane, Dania Badran, et al.
Neuro-Oncology Advances (2022) Vol. 4, Iss. 1
Open Access | Times Cited: 15
Efficient brain tumor detection and classification using magnetic resonance imaging
Revathi Sundarasekar, A. Ahilan
Biomedical Physics & Engineering Express (2021) Vol. 7, Iss. 5, pp. 055007-055007
Closed Access | Times Cited: 19
Development of a Novel Brain Tumor Classification Methodology Using Modified Deep Learning Principles
Pushpa Mohan, G. Ramkumar
(2024), pp. 1-7
Closed Access | Times Cited: 2
Anatomical Landmarks and DAG Network Learning for Alzheimer’s Disease Diagnosis
Zhu Tian, Chongfeng Cao, Zhishun Wang, et al.
IEEE Access (2020) Vol. 8, pp. 206063-206073
Open Access | Times Cited: 17
Brain tumor image segmentation using K-means and fuzzy C-means clustering
Munish Bhardwaj, Nafis Uddin Khan, Vikas Baghel, et al.
Elsevier eBooks (2023), pp. 293-316
Closed Access | Times Cited: 5
Brain Tumor Segmentation from Multi-spectral MR Image Data Using Random Forest Classifier
Szabolcs Csaholczi, Dávid Iclănzan, Levente Kovács, et al.
Lecture notes in computer science (2020), pp. 174-184
Closed Access | Times Cited: 9
Recognition of necrotic regions in MRI images of chronic spinal cord injury based on superpixel
Xing-Xing Bao, Can Zhao, Shu-Sheng Bao, et al.
Computer Methods and Programs in Biomedicine (2022) Vol. 228, pp. 107252-107252
Open Access | Times Cited: 6
Recent advancement in learning methodology for segmenting brain tumor from magnetic resonance imaging -a review
Sunayana G. Domadia, Falgunkumar N. Thakkar, Mayank A. Ardeshana
Multimedia Tools and Applications (2023) Vol. 82, Iss. 22, pp. 34809-34845
Closed Access | Times Cited: 3
Brain MR image tumor detection and classification using neuro fuzzy with binary cuckoo search technique
Selvapandian Arumugam, P. Sivakumar, Srikanth Prabhu
International Journal of Imaging Systems and Technology (2021) Vol. 31, Iss. 3, pp. 1185-1196
Closed Access | Times Cited: 6
Automatic Segmentation of Brain Tumor Parts from MRI Data Using a Random Forest Classifier
Szabolcs Csaholczi, Levente Kovács, László Szilágyi
(2021)
Closed Access | Times Cited: 6
Brain tumour classification: a comprehensive systematic review on various constraints
Chaithanyadas K.V, G. R. Gnana King
Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization (2022) Vol. 11, Iss. 3, pp. 517-529
Closed Access | Times Cited: 4
Brain Tumor Segmentation and Survival Prediction using Multimodal MRI Scans with Deep learning Algorithms
S. Anjanayya, V. M. Gayathri, R. Pitchai
2022 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES) (2022), pp. 1-5
Closed Access | Times Cited: 4
Iterative learning for maxillary sinus segmentation based on bounding box annotations
Xinli Xu, Kaidong Wang, Chengze Wang, et al.
Multimedia Tools and Applications (2023) Vol. 83, Iss. 11, pp. 33263-33293
Closed Access | Times Cited: 2
Automated Brain Tumor Classification and Detection Using Modified Convolutional Neural Networks for Early Diagnosis
Dinesh Rao Adithya, Rahul Rajendran, V. Sudha, et al.
(2023), pp. 351-355
Closed Access | Times Cited: 2
RETRACTED: Impact of Feature Selection for Data Classification Using Naive Bayes Classifier
Eman Hato
Journal of Physics Conference Series (2021) Vol. 1879, Iss. 2, pp. 022088-022088
Open Access | Times Cited: 5
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