Fully automated segmentation of clinical target volume in cervical cancer from magnetic resonance imaging with convolutional neural network-Reference-Cited by-同舟云学术

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Fully automated segmentation of clinical target volume in cervical cancer from magnetic resonance imaging with convolutional neural network

Published:2022-07-27 Issue:9 Volume:23 Page:
ISSN:1526-9914
Container-title:Journal of Applied Clinical Medical Physics
language:en
Short-container-title:J Applied Clin Med Phys

Author:

Zabihollahy Fatemeh¹,Viswanathan Akila N.¹,Schmidt Ehud J.²,Lee Junghoon¹

Affiliation:

1. Department of Radiation Oncology and Molecular Radiation Sciences Johns Hopkins University School of Medicine Baltimore Maryland USA

2. Division of Cardiology, Department of Medicine Johns Hopkins University School of Medicine Baltimore Maryland USA

Publisher

Wiley

Subject

Radiology, Nuclear Medicine and imaging,Instrumentation,Radiation

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/acm2.13725

Reference47 articles.

1. Combined external beam radiotherapy and vaginal brachytherapy versus vaginal brachytherapy in stage I, intermediate- and high-risk cases of endometrium carcinoma

2. Tumor volume discrepancies between FDG-PET and MRI for cervical cancer

3. The Added Role of MR Imaging in Treatment Stratification of Patients with Gynecologic Malignancies: What the Radiologist Needs to Know

4. Variability of clinical target volume delineation for definitive radiotherapy in cervix cancer

Cited by 14 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Cervical‐YOSA: Utilizing prompt engineering and pre‐trained large‐scale models for automated segmentation of multi‐sequence MRI images in cervical cancer;IET Image Processing;2024-09-05

2. Generalizability of deep learning in organ-at-risk segmentation: A transfer learning study in cervical brachytherapy;Radiotherapy and Oncology;2024-08

3. Cervical cancer segmentation based on medical images: a literature review;Quantitative Imaging in Medicine and Surgery;2024-07

4. Artificial intelligence in brachytherapy;Journal of Radiation Research and Applied Sciences;2024-06

5. Artificial Intelligence Uncertainty Quantification in Radiotherapy Applications - A Scoping Review;2024-05-13

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