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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.

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Showing 9 citing articles:

Brain tumor segmentation by cascaded multiscale multitask learning framework based on feature aggregation
Zahra Sobhaninia, Nader Karimi, Pejman Khadivi, et al.
Biomedical Signal Processing and Control (2023) Vol. 85, pp. 104834-104834
Closed Access | Times Cited: 18
Brain Tumor Classification Using Convolutional Neural Networks and Deep Learning
Szabolcs Csaholczi, Levente Kovács, László Szilágyi
(2024), pp. 000399-000404
Closed Access | Times Cited: 2
U-Net architecture variants for brain tumor segmentation of histogram corrected images
Szidónia Lefkovits, László Lefkovits
Acta Universitatis Sapientiae Informatica (2022) Vol. 14, Iss. 1, pp. 49-74
Open Access | Times Cited: 11
Segmentation of 6-month infant brain tissues from multi-spectral MRI records using a U-Net neural network architecture
Lehel Dénes-Fazakas, György Eigner, László Szilágyi
(2022), pp. 000077-000082
Closed Access | Times Cited: 3
A feature selection strategy using Markov clustering, for the optimization of brain tumor segmentation from MRI data
Ioan-Marius Pisak-Lukáts, Levente Kovács, László Szilágyi
Acta Universitatis Sapientiae Informatica (2022) Vol. 14, Iss. 2, pp. 316-337
Open Access | Times Cited: 3
Brain Tumor Segmentation from Multi-Spectral MRI Records Using a U-net Cascade Architecture
Ágnes Györfi, Levente Kovács, László Szilágyi
2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (2023), pp. 1327-1332
Closed Access | Times Cited: 1
A two-stage U-net approach to brain tumor segmentation from multi-spectral MRI records
Ágnes Györfi, Levente Kovács, László Szilágyi
Acta Universitatis Sapientiae Informatica (2022) Vol. 14, Iss. 2, pp. 223-247
Open Access | Times Cited: 2
Effect of spectral resolution on the segmentation quality of magnetic resonance imaging data
Ágnes Györfi, Szabolcs Csaholczi, Ioan-Marius Lukats-Pisak, et al.
(2022), pp. 000053-000058
Closed Access | Times Cited: 1
Challenges and Difficulties of Multi-Spectral MRI Based Brain Tumor Detection and Segmentation
László Szilágyi, Ágnes Györfi, Lehel Dénes-Fazakas, et al.
(2023), pp. 1-6
Closed Access
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