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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:

Integrating multiparametric MRI radiomics features and the Vesical Imaging-Reporting and Data System (VI-RADS) for bladder cancer grading
Zongtai Zheng, Feijia Xu, Zhuoran Gu, et al.
Abdominal Radiology (2021)
Closed Access | Times Cited: 26

Showing 1-25 of 26 citing articles:

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
Progress of Multiparameter Magnetic Resonance Imaging in Bladder Cancer: A Comprehensive Literature Review
Kangwen He, Xiaoyan Meng, Yanchun Wang, et al.
Diagnostics (2024) Vol. 14, Iss. 4, pp. 442-442
Open Access | Times Cited: 6
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
Radiomics-guided radiation therapy: opportunities and challenges
Hamid Abdollahi, Erika Chin, Haley Clark, et al.
Physics in Medicine and Biology (2022) Vol. 67, Iss. 12, pp. 12TR02-12TR02
Open Access | Times Cited: 20
Predicting muscle invasion in bladder cancer by deep learning analysis of MRI: comparison with vesical imaging–reporting and data system
Jianpeng Li, Kangyang Cao, Hongxin Lin, et al.
European Radiology (2022) Vol. 33, Iss. 4, pp. 2699-2709
Closed Access | Times Cited: 20
CT-based deep learning radiomics nomogram for the prediction of pathological grade in bladder cancer: a multicenter study
Hongzheng Song, Shifeng Yang, Boyang Yu, et al.
Cancer Imaging (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 12
Radiomics to Detect Inflammation and Fibrosis on Magnetic Resonance Enterography in Stricturing Crohn’s Disease
Prathyush Chirra, Joseph Sleiman, Namita Gandhi, et al.
Journal of Crohn s and Colitis (2024)
Closed Access | Times Cited: 4
Multiparametric MRI for Bladder Cancer: A Practical Approach to the Clinical Application of VI-RADS
Martina Pecoraro, Stefano Cipollari, Emanuele Messina, et al.
Radiology (2025) Vol. 314, Iss. 3
Closed Access
An MRI-based radiomics nomogram in predicting histologic grade of non-muscle-invasive bladder cancer
Longchao Li, Jing Zhang, Xia Zhe, et al.
Frontiers in Oncology (2023) Vol. 13
Open Access | Times Cited: 9
Machine learning models combining computed tomography semantic features and selected clinical variables for accurate prediction of the pathological grade of bladder cancer
Zhikang Deng, Wentao Dong, Situ Xiong, et al.
Frontiers in Oncology (2023) Vol. 13
Open Access | Times Cited: 9
Magnetic resonance imaging-based radiomics signature for preoperative prediction of Ki67 expression in bladder cancer
Zongtai Zheng, Zhuoran Gu, Feijia Xu, et al.
Cancer Imaging (2021) Vol. 21, Iss. 1
Open Access | Times Cited: 23
MRI-Based Radiomics in Bladder Cancer: A Systematic Review and Radiomics Quality Score Assessment
Bianca Boca, Cosmin Caraiani, Teodora Telecan, et al.
Diagnostics (2023) Vol. 13, Iss. 13, pp. 2300-2300
Open Access | Times Cited: 8
Proposal for a New Vesical Imaging-Reporting and Data System (VI-RADS)-Based Algorithm for the Management of Bladder Cancer: A Paradigm Shift From the Current Transurethral Resection of Bladder Tumor (TURBT)-Dependent Practice
Satoru Taguchi, Masanaka Watanabe, Mitsuhiro Tambo, et al.
Clinical Genitourinary Cancer (2022) Vol. 20, Iss. 4, pp. e291-e295
Closed Access | Times Cited: 13
Application of contrast-enhanced ultrasound in diagnosis and grading of bladder urothelial carcinoma
Huiping Zhang, Rongxi Liang, Xueying Lin, et al.
BMC Medical Imaging (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 2
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
MRI-based radiomics analysis of bladder cancer: prediction of pathological grade and histological variant
Wei Wang, Kan Wang, Jianxing Qiu, et al.
Clinical Radiology (2023) Vol. 78, Iss. 11, pp. e889-e897
Closed Access | Times Cited: 2
The application value of multi-parameter cystoscope in improving the accuracy of preoperative bladder cancer grading
Qikai Wu, Lingkai Cai, Baorui Yuan, et al.
BMC Urology (2022) Vol. 22, Iss. 1
Open Access | Times Cited: 3
Compressed Sensing 3D T2WI Radiomics Model: Improving Diagnostic Performance in Muscle Invasion of Bladder Cancer
Shuo Li, Zhichang Fan, Junting Guo, et al.
(2024)
Closed Access
Prediction of histopathologic grades of bladder cancer with radiomics based on MRI: Comparison with traditional MRI
Longchao Li, Jing Zhang, Xia Zhe, et al.
Urologic Oncology Seminars and Original Investigations (2024) Vol. 42, Iss. 6, pp. 176.e9-176.e20
Open Access
Compressed sensing 3D T2WI radiomics model: improving diagnostic performance in muscle invasion of bladder cancer
Shuo Li, Zhichang Fan, Junting Guo, et al.
BMC Medical Imaging (2024) Vol. 24, Iss. 1
Open Access
Preoperative Prediction of Muscle Invasiveness in Bladder Cancer: The Role of 3D Volumetric Radiomics Using Diffusion-Weighted MRI, the VI-RADS Score, or a Combination of Both
Merve Şam Özdemir, Sena Azamat, Harun Özdemïr, et al.
Annals of Surgical Oncology (2024) Vol. 31, Iss. 9, pp. 5845-5850
Closed Access
Application of Artificial Intelligence in Abdominal Imaging
Ma Xiaohong, Feng Bing, Qi Zhang, et al.
(2024), pp. 181-191
Closed Access
Current Status of Magnetic Resonance Imaging Use in Bladder Cancer
Hyungwoo Ahn
Investigative Radiology (2024)
Closed Access
Radiomics‑Clinical model based on 99mTc-MDP SPECT/CT for distinguishing between bone metastasis and benign bone disease in tumor patients
Huili Wang, Jianfeng Qiu, Jindong Xie, et al.
Journal of Cancer Research and Clinical Oncology (2023) Vol. 149, Iss. 14, pp. 13353-13361
Closed Access | Times Cited: 1
Prediction of bladder cancer grade based on biparametric MRI radiomics: comparison with traditional MRI
Longchao Li, Jing Zhang, Xia Zhe, et al.
Research Square (Research Square) (2023)
Open Access
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