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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:

Three-Phase Automatic Brain Tumor Diagnosis System Using Patches Based Updated Run Length Region Growing Technique
T. Kalaiselvi, P. Kumarashankar, P. Sriramakrishnan
Journal of Digital Imaging (2019) Vol. 33, Iss. 2, pp. 465-479
Open Access | Times Cited: 29

Showing 1-25 of 29 citing articles:

An artificial intelligence framework and its bias for brain tumor segmentation: A narrative review
Suchismita Das, Gopal Krishna Nayak, Luca Saba, et al.
Computers in Biology and Medicine (2022) Vol. 143, pp. 105273-105273
Closed Access | Times Cited: 107
Knowledge based fuzzy c-means method for rapid brain tissues segmentation of magnetic resonance imaging scans with CUDA enabled GPU machine
Prajoona Valsalan, P. Sriramakrishnan, S. Sekar, et al.
Journal of Ambient Intelligence and Humanized Computing (2020)
Closed Access | Times Cited: 51
Brain tumor segmentation in MRI images using nonparametric localization and enhancement methods with U-net
Ahmet İlhan, Boran Şekeroğlu, Rahib H. Abiyev
International Journal of Computer Assisted Radiology and Surgery (2022) Vol. 17, Iss. 3, pp. 589-600
Closed Access | Times Cited: 38
DSNN: A DenseNet-Based SNN for Explainable Brain Disease Classification
Ziquan Zhu, Siyuan Lu, Shuihua Wang‎, et al.
Frontiers in Systems Neuroscience (2022) Vol. 16
Open Access | Times Cited: 24
Brain tumor detection and segmentation: Interactive framework with a visual interface and feedback facility for dynamically improved accuracy and trust
Kashfia Sailunaz, Deniz Beştepe, Sleiman Alhajj, et al.
PLoS ONE (2023) Vol. 18, Iss. 4, pp. e0284418-e0284418
Open Access | Times Cited: 15
RIBM3DU‐Net: Glioma tumour substructures segmentation in magnetic resonance images using residual‐inception block with modified 3D U‐Net architecture
Syedsafi Shajahan, P. Sriramakrishnan, T. Kalaiselvi
International Journal of Imaging Systems and Technology (2024) Vol. 34, Iss. 2
Closed Access | Times Cited: 5
Pseudo-deep unsupervised model-based clustering for brain tumor detection in magnetic resonance images
Rahman Farnoosh, Fatemeh Aghagoli
Applied Soft Computing (2025), pp. 112940-112940
Closed Access
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: 26
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: 17
Brain magnetic resonance images segmentation via improved mixtures of factor analyzers based on dynamic co-clustering
Rahman Farnoosh, Fatemeh Aghagoli
Neurocomputing (2024) Vol. 583, pp. 127551-127551
Closed Access | Times Cited: 2
A Review of Brain Tumor Segmentation Using MRIs from 2019 to 2023 (Statistical Information, Key Achievements, and Limitations)
Yasaman Zakeri, Babak Karasfi, Afsaneh Jalalian
Journal of Medical and Biological Engineering (2024) Vol. 44, Iss. 2, pp. 155-180
Closed Access | Times Cited: 2
A Systematic Study of Artificial Intelligence-Based Methods for Detecting Brain Tumors
Sanjeet Kumar, Urmila Pilania, Neha Nandal
Informatics and Automation (2023) Vol. 22, Iss. 3, pp. 541-575
Open Access | Times Cited: 6
Advancements of MRI-based Brain Tumor Segmentation from Traditional to Recent Trends: A Review
T. Kalaiselvi, S. Padmapriya, P. Sriramakrishnan, et al.
Current Medical Imaging Formerly Current Medical Imaging Reviews (2021) Vol. 18, Iss. 12, pp. 1261-1275
Closed Access | Times Cited: 14
PBTNet: A New Computer-Aided Diagnosis System for Detecting Primary Brain Tumors
Siyuan Lu, Suresh Chandra Satapathy, Shuihua Wang‎, et al.
Frontiers in Cell and Developmental Biology (2021) Vol. 9
Open Access | Times Cited: 8
An Automated Two-Stage Brain Tumour Diagnosis System Using SVM and Geodesic Distance-Based Colour Segmentation
S. Syedsafi, P. Sriramakrishnan, T. Kalaiselvi
Lecture notes in electrical engineering (2023), pp. 179-191
Closed Access | Times Cited: 3
Application of a Modified Combinational Approach to Brain Tumor Detection in MR Images
Rahman Farnoosh, Hamidreza Noushkaran
Journal of Digital Imaging (2022) Vol. 35, Iss. 6, pp. 1421-1432
Open Access | Times Cited: 5
Brain Tumor Segmentation from Multi-Spectral MRI Data Using Cascaded Ensemble Learning
Timea Fulop, Ágnes Györfi, Szabolcs Csaholczi, et al.
(2020), pp. 531-536
Open Access | Times Cited: 7
MR Image Block-Based Brain Tumour Detection Using GLCM Texture Features and SVM
S. Syedsafi, P. Sriramakrishnan, T. Kalaiselvi
Lecture notes in networks and systems (2023), pp. 211-225
Closed Access | Times Cited: 2
Data preprocessing techniques for MRI brain scans using deep learning models
T. Kalaiselvi, T. Anitha, P. Sriramakrishnan
Elsevier eBooks (2022), pp. 13-25
Closed Access | Times Cited: 3
Ocmael: An Optimal Corresponding Multimodal Adaptive Ensemble Learning Model for Brain Tumor Segmentation
Jiashu Xu
(2024)
Closed Access
FCM and CBAC based Brain Tumor Identification and Segmentation
K. Nagalakshmi, R. Maheswari, T. C. Jaanu Priya, et al.
Journal of Soft Computing Paradigm (2024) Vol. 6, Iss. 2, pp. 155-168
Open Access
U-InceptAtt: U-Net-Like Architecture with Inception Module Encoder-Decoder and Attention Bottleneck for Brain Tumor Segmentation
Ilyasse Aboussaleh, Jamal Riffi, Khalid El Fazazy, et al.
Studies in systems, decision and control (2024), pp. 615-625
Closed Access
A Novel Distance Transform for Brain Extraction from T1-W Magnetic Resonance Images (MRI) of Human Head
K. Ezhilarasan, Somasundaram Praveenkumar, K. Somasundaram, et al.
Springer proceedings in mathematics & statistics (2024), pp. 25-55
Closed Access
Fully automatic brain tumor extraction and tissue segmentation from multimodal MRI brain images
T. Kalaiselvi, Kalaichelvi Nagarajan
International Journal of Imaging Systems and Technology (2020) Vol. 31, Iss. 1, pp. 336-350
Closed Access | Times Cited: 3
Contemporary Technique for Detection of Brain Tumor in Fluid-Attenuated Inversion Recovery Magnetic Resonance Imaging (MRI) Images
K. Bhima, M. Neelakantappa, K. Dasaradh Ramaiah, et al.
Smart innovation, systems and technologies (2022), pp. 117-125
Closed Access | Times Cited: 2
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