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:
MRI‐Based Manual versus Automated Corpus Callosum Volumetric Measurements in Multiple Sclerosis
Michael Plattén, Juha Martola, Katharina Fink, et al.
Journal of Neuroimaging (2019) Vol. 30, Iss. 2, pp. 198-204
Closed Access | Times Cited: 8
Michael Plattén, Juha Martola, Katharina Fink, et al.
Journal of Neuroimaging (2019) Vol. 30, Iss. 2, pp. 198-204
Closed Access | Times Cited: 8
Showing 8 citing articles:
Deep Learning Corpus Callosum Segmentation as a Neurodegenerative Marker in Multiple Sclerosis
Michael Plattén, Irene Brusini, Olle Andersson, et al.
Journal of Neuroimaging (2021) Vol. 31, Iss. 3, pp. 493-500
Open Access | Times Cited: 24
Michael Plattén, Irene Brusini, Olle Andersson, et al.
Journal of Neuroimaging (2021) Vol. 31, Iss. 3, pp. 493-500
Open Access | Times Cited: 24
The effect of gadolinium-based contrast-agents on automated brain atrophy measurements by FreeSurfer in patients with multiple sclerosis
Ingrid Anne Lie, Emma Kerklingh, Kristin Wesnes, et al.
European Radiology (2022) Vol. 32, Iss. 5, pp. 3576-3587
Open Access | Times Cited: 11
Ingrid Anne Lie, Emma Kerklingh, Kristin Wesnes, et al.
European Radiology (2022) Vol. 32, Iss. 5, pp. 3576-3587
Open Access | Times Cited: 11
Automatic deep learning multicontrast corpus callosum segmentation in multiple sclerosis
Irene Brusini, Michael Plattén, Russell Ouellette, et al.
Journal of Neuroimaging (2022) Vol. 32, Iss. 3, pp. 459-470
Open Access | Times Cited: 11
Irene Brusini, Michael Plattén, Russell Ouellette, et al.
Journal of Neuroimaging (2022) Vol. 32, Iss. 3, pp. 459-470
Open Access | Times Cited: 11
CCsNeT: Automated Corpus Callosum segmentation using fully convolutional network based on U-Net
Anjali Chandra, Shrish Verma, Ajay Singh Raghuvanshi, et al.
Journal of Applied Biomedicine (2022) Vol. 42, Iss. 1, pp. 187-203
Closed Access | Times Cited: 9
Anjali Chandra, Shrish Verma, Ajay Singh Raghuvanshi, et al.
Journal of Applied Biomedicine (2022) Vol. 42, Iss. 1, pp. 187-203
Closed Access | Times Cited: 9
Prediction of subjective cognitive decline after corpus callosum infarction by an interpretable machine learning-derived early warning strategy
Yawen Xu, Xu Sun, Yanqun Liu, et al.
Frontiers in Neurology (2023) Vol. 14
Open Access | Times Cited: 4
Yawen Xu, Xu Sun, Yanqun Liu, et al.
Frontiers in Neurology (2023) Vol. 14
Open Access | Times Cited: 4
Deep Learning-Based Corpus Callosum Segmentation from Brain Images: A Review
Padmanabha Sarma, G. Saranya
Wireless Personal Communications (2024)
Closed Access
Padmanabha Sarma, G. Saranya
Wireless Personal Communications (2024)
Closed Access
Comparison of Manual Cross-Sectional Measurements and Automatic Volumetry of the Corpus Callosum, and Their Clinical Impact: A Study on Type 1 Diabetes and Healthy Controls
Tor-björn Claesson, Jukka Putaala, Sara Shams, et al.
Frontiers in Neurology (2020) Vol. 11
Open Access | Times Cited: 2
Tor-björn Claesson, Jukka Putaala, Sara Shams, et al.
Frontiers in Neurology (2020) Vol. 11
Open Access | Times Cited: 2
