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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:

Automatic segmentation of bladder cancer on MRI using a convolutional neural network and reproducibility of radiomics features: a two-center study
Yusaku Moribata, Yasuhisa Kurata, Mizuho Nishio, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 17

Showing 17 citing articles:

Pictorial review of multiparametric MRI in bladder urothelial carcinoma with variant histology: pearls and pitfalls
Yuki Arita, Sungmin Woo, Thomas C. Kwee, et al.
Abdominal Radiology (2024)
Closed Access | Times Cited: 6
Recent trends in AI applications for pelvic MRI: a comprehensive review
Takahiro Tsuboyama, Masahiro Yanagawa, Tomoyuki Fujioka, et al.
La radiologia medica (2024) Vol. 129, Iss. 9, pp. 1275-1287
Closed Access | Times Cited: 5
Label Distribution Learning for Automatic Cancer Grading of Histopathological Images of Prostate Cancer
Mizuho Nishio, H Matsuo, Yasuhisa Kurata, et al.
Cancers (2023) Vol. 15, Iss. 5, pp. 1535-1535
Open Access | Times Cited: 12
Multiparametric MRI and artificial intelligence in predicting and monitoring treatment response in bladder cancer
Yuki Arita, Thomas C. Kwee, Oğuz Akın, et al.
Insights into Imaging (2025) Vol. 16, Iss. 1
Open Access
An accurate and trustworthy deep learning approach for bladder tumor segmentation with uncertainty estimation
Jie Xu, Haixin Wang, Min Lü, et al.
Computer Methods and Programs in Biomedicine (2025) Vol. 263, pp. 108645-108645
Closed Access
Imaging Genomics and Multiomics: A Guide for Beginners Starting Radiomics-Based Research
Shiva M. Singh, Bahram Mohajer, Shane A. Wells, et al.
Academic Radiology (2024) Vol. 31, Iss. 6, pp. 2281-2291
Closed Access | Times Cited: 3
Boundary guidance network for medical image segmentation
Rubin Xu, Chao Xu, Zhengping Li, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 3
A review of Artificial Intelligence methods in bladder cancer: segmentation, classification, and detection
Ayah Bashkami, Ahmad Nasayreh, Sharif Naser Makhadmeh, et al.
Artificial Intelligence Review (2024) Vol. 57, Iss. 12
Open Access | Times Cited: 3
AI-powered radiomics: revolutionizing detection of urologic malignancies
David G. Gelikman, Soroush Rais‐Bahrami, Peter A. Pinto, et al.
Current Opinion in Urology (2023) Vol. 34, Iss. 1, pp. 1-7
Closed Access | Times Cited: 5
Multiparametric MRI in Era of Artificial Intelligence for Bladder Cancer Therapies
Oğuz Akın, Alfonso Lema-Dopico, Ramesh Paudyal, et al.
Cancers (2023) Vol. 15, Iss. 22, pp. 5468-5468
Open Access | Times Cited: 5
LCANet: A Lightweight Context-Aware Network for Bladder Tumor Segmentation in MRI Images
Yixing Wang, Xiang Li, Xiufen Ye
Mathematics (2023) Vol. 11, Iss. 10, pp. 2357-2357
Open Access | Times Cited: 4
Radiomics Prediction of Muscle Invasion in Bladder Cancer Using Semi-Automatic Lesion Segmentation of MRI Compared with Manual Segmentation
Yaojiang Ye, Zixin Luo, Zhengxuan Qiu, et al.
Bioengineering (2023) Vol. 10, Iss. 12, pp. 1355-1355
Open Access | Times Cited: 4
Deep Learning Algorithms for Bladder Cancer Segmentation on Multi-Parametric MRI
Kazım Gümüş, Julien Nicolas, Dheeraj Reddy Gopireddy, et al.
Cancers (2024) Vol. 16, Iss. 13, pp. 2348-2348
Open Access | Times Cited: 1
Development of deep learning model for diagnosing muscle-invasive bladder cancer on MRI with vision transformer
Yasuhisa Kurata, Mizuho Nishio, Yusaku Moribata, et al.
Heliyon (2024) Vol. 10, Iss. 16, pp. e36144-e36144
Open Access | Times Cited: 1
AI-based automated segmentation for ovarian/adnexal masses and their internal components on ultrasound imaging
Heather M. Whitney, Roni Yoeli‐Bik, Jacques S. Abramowicz, et al.
Journal of Medical Imaging (2024) Vol. 11, Iss. 04
Open Access
Using CT images to assist the segmentation of MR images via generalization: Segmentation of the renal parenchyma of renal carcinoma patients
Zhengyang Yu, Tongtong Zhao, Zuqiang Xi, et al.
Medical Physics (2024) Vol. 52, Iss. 2, pp. 951-964
Closed Access
Development of Pericardial Fat Count Images Using a Combination of Three Different Deep-Learning Models: Image Translation Model From Chest Radiograph Image to Projection Image of Three-Dimensional Computed Tomography
Takaaki Matsunaga, Atsushi K. Kono, H Matsuo, et al.
Academic Radiology (2023) Vol. 31, Iss. 3, pp. 822-829
Closed Access
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