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:
Deep learning aided oropharyngeal cancer segmentation with adaptive thresholding for predicted tumor probability in FDG PET and CT images
Alessia de Biase, Nanna M. Sijtsema, Lisanne V. van Dijk, et al.
Physics in Medicine and Biology (2023) Vol. 68, Iss. 5, pp. 055013-055013
Open Access | Times Cited: 20
Alessia de Biase, Nanna M. Sijtsema, Lisanne V. van Dijk, et al.
Physics in Medicine and Biology (2023) Vol. 68, Iss. 5, pp. 055013-055013
Open Access | Times Cited: 20
Showing 20 citing articles:
PET/CT based transformer model for multi-outcome prediction in oropharyngeal cancer
Baoqiang Ma, Jiapan Guo, Alessia de Biase, et al.
Radiotherapy and Oncology (2024) Vol. 197, pp. 110368-110368
Closed Access | Times Cited: 5
Baoqiang Ma, Jiapan Guo, Alessia de Biase, et al.
Radiotherapy and Oncology (2024) Vol. 197, pp. 110368-110368
Closed Access | Times Cited: 5
Deep learning-based outcome prediction using PET/CT and automatically predicted probability maps of primary tumor in patients with oropharyngeal cancer
Alessia de Biase, Baoqiang Ma, Jiapan Guo, et al.
Computer Methods and Programs in Biomedicine (2023) Vol. 244, pp. 107939-107939
Open Access | Times Cited: 13
Alessia de Biase, Baoqiang Ma, Jiapan Guo, et al.
Computer Methods and Programs in Biomedicine (2023) Vol. 244, pp. 107939-107939
Open Access | Times Cited: 13
Artificial intelligence uncertainty quantification in radiotherapy applications − A scoping review
Kareem A. Wahid, Zaphanlene Kaffey, David P. Farris, et al.
Radiotherapy and Oncology (2024) Vol. 201, pp. 110542-110542
Open Access | Times Cited: 4
Kareem A. Wahid, Zaphanlene Kaffey, David P. Farris, et al.
Radiotherapy and Oncology (2024) Vol. 201, pp. 110542-110542
Open Access | Times Cited: 4
The prognostic value of pathologic lymph node imaging using deep learning-based outcome prediction in oropharyngeal cancer patients
Baoqiang Ma, Alessia de Biase, Jiapan Guo, et al.
Physics and Imaging in Radiation Oncology (2025) Vol. 33, pp. 100733-100733
Open Access
Baoqiang Ma, Alessia de Biase, Jiapan Guo, et al.
Physics and Imaging in Radiation Oncology (2025) Vol. 33, pp. 100733-100733
Open Access
Gross tumor volume confidence maps prediction for soft tissue sarcomas from multi-modality medical images using a diffusion model
Yafei Dong, Thibault Marin, Yue Zhuo, et al.
Physics and Imaging in Radiation Oncology (2025) Vol. 33, pp. 100734-100734
Open Access
Yafei Dong, Thibault Marin, Yue Zhuo, et al.
Physics and Imaging in Radiation Oncology (2025) Vol. 33, pp. 100734-100734
Open Access
Uncertainty-Aware Deep Learning for Segmentation of Primary Tumor and Pathologic Lymph Nodes in Oropharyngeal Cancer: Insights from a Multi-Center Cohort
Alessia de Biase, Nanna M. Sijtsema, Lisanne V. van Dijk, et al.
Computerized Medical Imaging and Graphics (2025), pp. 102535-102535
Open Access
Alessia de Biase, Nanna M. Sijtsema, Lisanne V. van Dijk, et al.
Computerized Medical Imaging and Graphics (2025), pp. 102535-102535
Open Access
Harnessing uncertainty in radiotherapy auto-segmentation quality assurance
Kareem A. Wahid, Jaakko Sahlsten, Joel Jaskari, et al.
Physics and Imaging in Radiation Oncology (2023) Vol. 29, pp. 100526-100526
Open Access | Times Cited: 8
Kareem A. Wahid, Jaakko Sahlsten, Joel Jaskari, et al.
Physics and Imaging in Radiation Oncology (2023) Vol. 29, pp. 100526-100526
Open Access | Times Cited: 8
Application of simultaneous uncertainty quantification for image segmentation with probabilistic deep learning: Performance benchmarking of oropharyngeal cancer target delineation as a use-case
Jaakko Sahlsten, Joel Jaskari, Kareem A. Wahid, et al.
medRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 7
Jaakko Sahlsten, Joel Jaskari, Kareem A. Wahid, et al.
medRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 7
Uncertainty-Aware Deep Learning for Segmentation of Primary Tumour and Pathologic Lymph Nodes in Oropharyngeal Cancer: Insights from a Multi-Centre Cohort
Alessia de Biase, Nanna M. Sijtsema, Lisanne V. van Dijk, et al.
Research Square (Research Square) (2024)
Open Access | Times Cited: 2
Alessia de Biase, Nanna M. Sijtsema, Lisanne V. van Dijk, et al.
Research Square (Research Square) (2024)
Open Access | Times Cited: 2
Probability maps for deep learning-based head and neck tumor segmentation: Graphical User Interface design and test
Alessia de Biase, Liv Ziegfeld, Nanna M. Sijtsema, et al.
Computers in Biology and Medicine (2024) Vol. 177, pp. 108675-108675
Open Access | Times Cited: 2
Alessia de Biase, Liv Ziegfeld, Nanna M. Sijtsema, et al.
Computers in Biology and Medicine (2024) Vol. 177, pp. 108675-108675
Open Access | Times Cited: 2
Application of simultaneous uncertainty quantification and segmentation for oropharyngeal cancer use-case with Bayesian deep learning
Jaakko Sahlsten, Joel Jaskari, Kareem A. Wahid, et al.
Communications Medicine (2024) Vol. 4, Iss. 1
Open Access | Times Cited: 2
Jaakko Sahlsten, Joel Jaskari, Kareem A. Wahid, et al.
Communications Medicine (2024) Vol. 4, Iss. 1
Open Access | Times Cited: 2
Enhancing the reliability of deep learning-based head and neck tumour segmentation using uncertainty estimation with multi-modal images
Jintao Ren, Jonas Teuwen, Jasper Nijkamp, et al.
Physics in Medicine and Biology (2024) Vol. 69, Iss. 16, pp. 165018-165018
Open Access | Times Cited: 2
Jintao Ren, Jonas Teuwen, Jasper Nijkamp, et al.
Physics in Medicine and Biology (2024) Vol. 69, Iss. 16, pp. 165018-165018
Open Access | Times Cited: 2
Dose distribution prediction for head-and-neck cancer radiotherapy using a generative adversarial network: influence of input data
Xiaojin Gu, Victor I. J. Strijbis, Ben J. Slotman, et al.
Frontiers in Oncology (2023) Vol. 13
Open Access | Times Cited: 6
Xiaojin Gu, Victor I. J. Strijbis, Ben J. Slotman, et al.
Frontiers in Oncology (2023) Vol. 13
Open Access | Times Cited: 6
Segmentation and quantitative analysis of optical coherence tomography (OCT) images of laser burned skin based on deep learning
Jingyuan Wu, Qiong Ma, Xun Zhou, et al.
Biomedical Physics & Engineering Express (2024) Vol. 10, Iss. 4, pp. 045026-045026
Open Access | Times Cited: 1
Jingyuan Wu, Qiong Ma, Xun Zhou, et al.
Biomedical Physics & Engineering Express (2024) Vol. 10, Iss. 4, pp. 045026-045026
Open Access | Times Cited: 1
Recommendations for the creation of benchmark datasets for reproducible artificial intelligence in radiology
Nikos Sourlos, Rozemarijn Vliegenthart, João Santinha, et al.
Insights into Imaging (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 1
Nikos Sourlos, Rozemarijn Vliegenthart, João Santinha, et al.
Insights into Imaging (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 1
Multi-modal tumor segmentation methods based on deep learning: a narrative review
Hengzhi Xue, Yudong Yao, Yueyang Teng
Quantitative Imaging in Medicine and Surgery (2023) Vol. 14, Iss. 1, pp. 1122-1140
Open Access | Times Cited: 4
Hengzhi Xue, Yudong Yao, Yueyang Teng
Quantitative Imaging in Medicine and Surgery (2023) Vol. 14, Iss. 1, pp. 1122-1140
Open Access | Times Cited: 4
Deep Learning Techniques and Imaging in Otorhinolaryngology—A State-of-the-Art Review
Christos Tsilivigkos, Michail Athanasopoulos, Riccardo Di Micco, et al.
Journal of Clinical Medicine (2023) Vol. 12, Iss. 22, pp. 6973-6973
Open Access | Times Cited: 3
Christos Tsilivigkos, Michail Athanasopoulos, Riccardo Di Micco, et al.
Journal of Clinical Medicine (2023) Vol. 12, Iss. 22, pp. 6973-6973
Open Access | Times Cited: 3
Artificial Intelligence Uncertainty Quantification in Radiotherapy Applications - A Scoping Review
Kareem A. Wahid, Zaphanlene Kaffey, David P. Farris, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Kareem A. Wahid, Zaphanlene Kaffey, David P. Farris, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Efficient model-informed co-segmentation of tumors on PET/CT driven by clustering and classification information
Laquan Li, Chuangbo Jiang, Lei Yu, et al.
Computers in Biology and Medicine (2024) Vol. 180, pp. 108980-108980
Closed Access
Laquan Li, Chuangbo Jiang, Lei Yu, et al.
Computers in Biology and Medicine (2024) Vol. 180, pp. 108980-108980
Closed Access
Deep learning-based multi-stage postoperative type-b aortic dissection segmentation using global-local fusion learning
Xuyang Zhang, Guoliang Cheng, Xiaofeng Han, et al.
Physics in Medicine and Biology (2023) Vol. 68, Iss. 23, pp. 235011-235011
Closed Access | Times Cited: 1
Xuyang Zhang, Guoliang Cheng, Xiaofeng Han, et al.
Physics in Medicine and Biology (2023) Vol. 68, Iss. 23, pp. 235011-235011
Closed Access | Times Cited: 1
A Dual-branch Framework Based on Implicit Continuous Representation for Tumor Image Segmentation
Jing Wang, Yuanjie Zheng, Junxia Wang, et al.
Research Square (Research Square) (2023)
Open Access
Jing Wang, Yuanjie Zheng, Junxia Wang, et al.
Research Square (Research Square) (2023)
Open Access
