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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:

Brain Tumor Segmentation from 3D MRI Scans Using U-Net
Sidratul Montaha, Sami Azam, A. K. M. Rakibul Haque Rafid, et al.
SN Computer Science (2023) Vol. 4, Iss. 4
Open Access | Times Cited: 24

Showing 24 citing articles:

A systematic analysis of magnetic resonance images and deep learning methods used for diagnosis of brain tumor
Shubhangi Solanki, Uday Pratap Singh, Siddharth Singh Chouhan, et al.
Multimedia Tools and Applications (2023) Vol. 83, Iss. 8, pp. 23929-23966
Closed Access | Times Cited: 28
TransSea: Hybrid CNN-Transformer with Semantic Awareness for 3D Brain Tumor Segmentation
Yü Liu, Yize Ma, Zhiqin Zhu, et al.
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 16-31
Closed Access | Times Cited: 6
Improved Brain Tumor Segmentation Using UNet-LSTM Architecture
S. Saran Raj, K Logeshwaran, Anisha Devi Kalluri, et al.
SN Computer Science (2024) Vol. 5, Iss. 5
Closed Access | Times Cited: 5
XAI-MRI: an ensemble dual-modality approach for 3D brain tumor segmentation using magnetic resonance imaging
Ahmeed Suliman Farhan, Muhammad Khalid, Umar Manzoor
Frontiers in Artificial Intelligence (2025) Vol. 8
Open Access
Local interpretable model-agnostic explanations guided brain magnetic resonance imaging classification for identifying attention deficit hyperactivity disorder subtypes
K. Usha Rupni, P. Aruna Priya
Journal of Ambient Intelligence and Humanized Computing (2025)
Closed Access
From Traditional Methods to 3D U-Net: A Comprehensive Review of Brain Tumour Segmentation Techniques
Mohammed A. Saleh, Musab Elkheir Salih, Mohamed A. A. Ahmed, et al.
Journal of Biomedical Science and Engineering (2025) Vol. 18, Iss. 01, pp. 1-32
Open Access
Encoding 3D information in 2D feature maps for brain CT-Angiography
Uma Maria Lal-Trehan Estrada, Sunil A. Sheth, Arnau Oliver, et al.
Computerized Medical Imaging and Graphics (2025) Vol. 122, pp. 102518-102518
Open Access
Brain Tumor Segmentation and Classification Using Binomial Thresholding-Based Bidirectional-Long-Short Term Memory
J. Shreeharsha
International journal of intelligent engineering and systems (2024) Vol. 17, Iss. 3, pp. 149-158
Open Access | Times Cited: 3
Enhancing brain tumor segmentation in MRI images using the IC-net algorithm framework
C. S., J. Christopher Clement
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 3
High-Resolution Model for Segmenting and Predicting Brain Tumor Based on Deep UNet with Multi Attention Mechanism
Hanaa Al Abboodi, Amera W. Al-funjan, Ahmed Aldhahab, et al.
International journal of intelligent engineering and systems (2024) Vol. 17, Iss. 2, pp. 294-310
Open Access | Times Cited: 2
Optimal feature subset selection for MRI brain tumor classification using improved ant-lion optimization
Sangeetha Saman, Swathi Jamjala Narayanan
Evolutionary Intelligence (2024)
Closed Access | Times Cited: 2
Semantic segmentation of brain tumor images using attention-based residual light u-net model
Chakrapani Chakrapani, Sunil Kumar
Multimedia Tools and Applications (2024)
Closed Access | Times Cited: 1
G-Net: Implementing an enhanced brain tumor segmentation framework using semantic segmentation design
C. S., Christopher Clement
PLoS ONE (2024) Vol. 19, Iss. 8, pp. e0308236-e0308236
Open Access | Times Cited: 1
An Investigation of Transfer Learning Approaches to Overcome Limited Labeled Data in Medical Image Analysis
Jinyeong Chae, Jihie Kim
Applied Sciences (2023) Vol. 13, Iss. 15, pp. 8671-8671
Open Access | Times Cited: 3
A diagnosis model for brain atrophy using deep learning and MRI of type 2 diabetes mellitus
Syed Saba Raoof, M.A. Saleem Durai
Frontiers in Neuroscience (2023) Vol. 17
Open Access | Times Cited: 3
Advancing Brain Tumor Segmentation via Attention-Based 3D U-Net Architecture and Digital Image Processing
Eyad Gad, Seif Soliman, M. Saeed Darweesh
Lecture notes in computer science (2023), pp. 245-258
Closed Access | Times Cited: 2
From Imaging to Insights: A Review of Techniques for Brain Tumor Analysis
K. Tejaswi, M. Varshitha, G. Kavita
Algorithms for intelligent systems (2024), pp. 585-598
Closed Access
Deep learning based 3D multimodal CNN for brain tumor segmentation and detection
Aniket Tiwari, Divyansh Kumar, Hanuman Sidh, et al.
Iran Journal of Computer Science (2024)
Closed Access
Brain Tumor Segmentation from Optimal MRI Slices Using a Lightweight U-Net
Fernando Daniel Hernandez-Gutierrez, Eli Gabriel Avina-Bravo, Daniel F. Zambrano-Gutierrez, et al.
Technologies (2024) Vol. 12, Iss. 10, pp. 183-183
Open Access
Medical Image Segmentation by Improved Nested Unet
Song-Toan Tran, Minh-Hai Le, Thai‐Son Nguyen, et al.
Communications in computer and information science (2024), pp. 114-125
Closed Access
XAI-MRI: An Ensemble Dual-Modality Approach for 3D Brain Tumor Segmentation Using Magnetic Resonance Imaging
Ahmeed Suliman Farhan, Muhammad Khalid, Umar Manzoor
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Multi-class Semantic Segmentation: A Deep Supervised Approach For Brain Tumor Detection Using 3D U-Net++ Architecture
Rajarshi Saha, Debosmit Neogi, Rapti Chaudhuri, et al.
Lecture notes in networks and systems (2024), pp. 39-51
Closed Access
CNN-based Deep Learning Approach for MRI-based Brain Tumor Detection
Kanagaraj Narayanasamy, Elangovan Elangovan, Sathish Kumar L, et al.
(2023), pp. 875-879
Closed Access
Brain Tumor Segmentation using the Modified UNET Architecture
Harsh Garg, Ramavath Vasanth Naik, Tarun Harishchandra Pal, et al.
2022 IEEE 6th Conference on Information and Communication Technology (CICT) (2023), pp. 1-6
Closed Access
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