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References from A lightweight deep learning model for automated segmentation of Gynecologic organs and cervical Tumors on T2-weighted magnetic resonance imaging. Local targets link to admitted publications; unresolved targets remain external evidence.
Cancer statistics for the year 2020: an overview
10.1002/ijc.33588 · 2021 · External reference
Human papillomavirus and cervical cancer
10.1128/cmr.16.1.1-17.2003 · 2003 · External reference
Global estimates of incidence and mortality of cervical cancer in 2020: a baseline analysis of the WHO global cervical Cancer elimination initiative
10.1016/s2214-109x(22)00501-0 · 2023 · External reference
The role of imaging in cervical cancer staging: ESGO/ESTRO/ESP guidelines (update 2023)
10.3390/cancers16040775 · 2024 · External reference
Fully automated segmentation of clinical target volume in cervical cancer from magnetic resonance imaging with convolutional neural network
10.1002/acm2.13725 · 2022 · External reference
Adaptive management of cervical cancer radiotherapy
10.1016/j.semradonc.2009.11.006 · 2010 · External reference
Image guided adaptive brachytherapy with combined intracavitary and interstitial technique improves the therapeutic ratio in locally advanced cervical cancer
10.1016/j.radonc.2016.03.020 · 2016 · External reference
Diagnosing uterine cervical cancer on a single T2-weighted image: comparison between deep learning versus radiologists
10.1016/j.ejrad.2020.109471 · 2021 · External reference
Deep learning-based auto-segmentation of clinical target volumes for radiotherapy treatment of cervical cancer
10.1002/acm2.13470 · 2022 · External reference
Development and validation of a deep learning algorithm for auto-delineation of clinical target volume and organs at risk in cervical cancer radiotherapy
10.1016/j.radonc.2020.09.060 · 2020 · External reference
10.1038/s41592-020-01008-z · 2021 · Admitted local publication
PocketNet: a smaller neural network for medical image analysis
10.1109/tmi.2022.3224873 · 2023 · External reference
Cervical cancer – tumor heterogeneity: serial functional and molecular imaging across the radiation therapy course in advanced cervical cancer [dataset]
2023 · External reference
Comprehensive clinical evaluation of deep learning-based auto-segmentation for radiotherapy in patients with cervical cancer
10.3389/fonc.2023.1119008 · 2023 · External reference
Automatic contour segmentation of cervical cancer using artificial intelligence
10.1093/jrr/rrab070 · 2021 · External reference
Fully automatic whole-volume tumor segmentation in cervical cancer
10.3390/cancers14102372 · 2022 · External reference
Deep learning for fully automated tumor segmentation and extraction of magnetic resonance radiomics features in cervical cancer
10.1007/s00330-019-06467-3 · 2020 · External reference
Automatic segmentation using deep learning to enable online dose optimization during adaptive radiation therapy of cervical cancer
10.1016/j.ijrobp.2020.10.038 · 2021 · External reference
Diffusion weighted imaging for gross tumor volume delineation in primary radiochemotherapy and image guided adaptive brachytherapy for cervical cancer
10.1016/j.radonc.2025.111306 · 2026 · External reference
