Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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 uterine endometrial cancer on multi-sequence MRI using a convolutional neural network
Yasuhisa Kurata, Mizuho Nishio, Yusaku Moribata, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 31

Showing 1-25 of 31 citing articles:

An overview of deep learning in medical imaging
Andrés Anaya-Isaza, Leonel Mera-Jiménez, Martha Zequera-Diaz
Informatics in Medicine Unlocked (2021) Vol. 26, pp. 100723-100723
Open Access | Times Cited: 95
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
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
Fully Automatic Whole-Volume Tumor Segmentation in Cervical Cancer
Erlend Hodneland, Satheshkumar Kaliyugarasan, Kari S. Wagner‐Larsen, et al.
Cancers (2022) Vol. 14, Iss. 10, pp. 2372-2372
Open Access | Times Cited: 21
Evaluating the quality of radiomics-based studies for endometrial cancer using RQS and METRICS tools
Luca Russo, Silvia Bottazzi, Burak Koçak, et al.
European Radiology (2024) Vol. 35, Iss. 1, pp. 202-214
Open Access | Times Cited: 4
MRI‐based radiomics nomogram for the preoperative prediction of deep myometrial invasion of FIGO stage I endometrial carcinoma
Mingli Zhao, Feng Wen, Jiaxin Shi, et al.
Medical Physics (2022) Vol. 49, Iss. 10, pp. 6505-6516
Closed Access | Times Cited: 18
The stability of oncologic MRI radiomic features and the potential role of deep learning: a review
Elisa Scalco, Giovanna Rizzo, Alfonso Mastropietro
Physics in Medicine and Biology (2022) Vol. 67, Iss. 9, pp. 09TR03-09TR03
Closed Access | Times Cited: 17
Generalizable transfer learning of automated tumor segmentation from cervical cancers toward a universal model for uterine malignancies in diffusion-weighted MRI
Yu‐Chun Lin, Yenpo Lin, Yen-Ling Huang, et al.
Insights into Imaging (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 10
Cer-ConvN3Unet: an end-to-end multi-parametric MRI-based pipeline for automated detection and segmentation of cervical cancer
Shudong Xia, Bo Zhao, Yingming Li, et al.
European Radiology Experimental (2025) Vol. 9, Iss. 1
Open Access
Artificial intelligence in the diagnosis and management of gynecologic cancer
Chaiyawut Paiboonborirak, Nadeem R. Abu‐Rustum, Sarikapan Wilailak
International Journal of Gynecology & Obstetrics (2025)
Open Access
Preoperative Tumor Texture Analysis on MRI for High-Risk Disease Prediction in Endometrial Cancer: A Hypothesis-Generating Study
Maura Miccò, Benedetta Gui, Luca Russo, et al.
Journal of Personalized Medicine (2022) Vol. 12, Iss. 11, pp. 1854-1854
Open Access | Times Cited: 11
Automated Detection of Endometrial Polyps from Hysteroscopic Videos Using Deep Learning
Aihua Zhao, Xin Du, Suzhen Yuan, et al.
Diagnostics (2023) Vol. 13, Iss. 8, pp. 1409-1409
Open Access | Times Cited: 6
Weakly supervised segmentation of uterus by scribble labeling on endometrial cancer MR images
Jie Ying, Wei Huang, Le Fu, et al.
Computers in Biology and Medicine (2023) Vol. 167, pp. 107582-107582
Closed Access | Times Cited: 5
Preoperative Imaging Evaluation of Endometrial Cancer in FIGO 2023
Aki Kido, Yuki Himoto, Yasuhisa Kurata, et al.
Journal of Magnetic Resonance Imaging (2023) Vol. 60, Iss. 4, pp. 1225-1242
Closed Access | Times Cited: 5
Artificial Intelligence and Radiomics for Endometrial Cancer MRI: Exploring the Whats, Whys and Hows
Elisabetta Leo, Arnaldo Stanzione, Mariaelena Miele, et al.
Journal of Clinical Medicine (2023) Vol. 13, Iss. 1, pp. 226-226
Open Access | Times Cited: 5
The Effects of Automatic Segmentations on Preoperative Lymph Node Status Prediction Models With Ultrasound Radiomics for Patients With Early Stage Cervical Cancer
Yinyan Teng, Yao Ai, Liang Tao, et al.
Technology in Cancer Research & Treatment (2022) Vol. 21
Open Access | Times Cited: 9
Clinical Utility of Diffusion-Weighted Imaging in Gynecological Imaging
Shinya Fujii, Takuro Gonda, Hiroto Yunaga
Investigative Radiology (2023) Vol. 59, Iss. 1, pp. 78-91
Closed Access | Times Cited: 5
Enhancing brain tumor classification with transfer learning: Leveraging DenseNet121 for accurate and efficient detection
Asif Raza, Mohammed S. Alshehri, Sultan Almakdi, et al.
International Journal of Imaging Systems and Technology (2023) Vol. 34, Iss. 1
Open Access | Times Cited: 4
Developing and Evaluating Deep Learning Algorithms for Object Detection: Key Points for Achieving Superior Model Performance
Jang-Hoon Oh, Hyug‐Gi Kim, Kyung Mi Lee
Korean Journal of Radiology (2023) Vol. 24, Iss. 7, pp. 698-698
Open Access | Times Cited: 4
Artificial Intelligence in Obstetric and Gynecological MR Imaging
Tsukasa Saida, Wenchao Gu, Sodai Hoshiai, et al.
Magnetic Resonance in Medical Sciences (2024)
Open Access | Times Cited: 1
Advances in Radiomics Research for Endometrial Cancer: A Comprehensive Review
Wenxiu Guo, Tong Wang, Binglin Lv, et al.
Journal of Cancer (2023) Vol. 14, Iss. 18, pp. 3523-3531
Open Access | Times Cited: 3
Artificial intelligence in female pelvic oncology: tailoring applications to clinical needs
Luca Russo, Silvia Bottazzi, Evis Sala
European Radiology (2023) Vol. 34, Iss. 6, pp. 4038-4040
Closed Access | Times Cited: 3
Multi-parametric MRI-based radiomics for preoperative prediction of multiple biological characteristics in endometrial cancer
Changjun Ma, Ying Zhao, Qingling Song, et al.
Frontiers in Oncology (2023) Vol. 13
Open Access | Times Cited: 3
18F-FDG PET/MRI in endometrial cancer: systematic review and meta-analysis
Carolina Bezzi, Enrica Zambella, Samuele Ghezzo, et al.
Clinical and Translational Imaging (2021) Vol. 10, Iss. 1, pp. 45-58
Closed Access | Times Cited: 6
Dual deterministic model based on deep neural network for the classification of pneumonia
Muhammad Mustafa Khan, Muhammad Saif ul Islam, Ali Akbar Siddiqui, et al.
Intelligent Decision Technologies (2023) Vol. 17, Iss. 3, pp. 641-654
Closed Access | Times Cited: 2
Page 1 - Next Page

Scroll to top