Clinical application and improvement of a CNN‐based autosegmentation model for clinical target volumes in cervical cancer radiotherapy-Reference-Cited by-同舟云学术

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Clinical application and improvement of a CNN‐based autosegmentation model for clinical target volumes in cervical cancer radiotherapy

Published:2021-10-13 Issue:11 Volume:22 Page:115-125
ISSN:1526-9914
Container-title:Journal of Applied Clinical Medical Physics
language:en
Short-container-title:J Appl Clin Med Phys

Author:

Chang Yankui¹,Wang Zhi¹²,Peng Zhao¹,Zhou Jieping³,Pi Yifei⁴,Xu X. George¹³,Pei Xi¹⁵

Affiliation:

1. Institute of Nuclear Medical Physics University of Science and Technology of China Hefei China

2. Radiation Oncology Department First Affiliated Hospital of Anhui Medical University Hefei China

3. Radiation Oncology Department First Affiliated Hospital of University of Science and Technology of China Hefei China

4. Radiation Oncology Department First Affiliated Hospital of Zhengzhou University Zhengzhou China

5. Anhui Wisdom Technology Co., Ltd. Hefei Anhui China

Funder

Natural Science Foundation of Anhui Province

Publisher

Wiley

Subject

Radiology Nuclear Medicine and imaging,Instrumentation,Radiation

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/acm2.13440

Reference29 articles.

1. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

2. Comparative clinical evaluation of atlas and deep-learning-based auto-segmentation of organ structures in liver cancer

3. A novel MRI segmentation method using CNN ‐based correction network for MRI ‐guided adaptive radiotherapy

4. Technical Note: More accurate and efficient segmentation of organs‐at‐risk in radiotherapy with convolutional neural networks cascades

5. Segmentation of organs-at-risks in head and neck CT images using convolutional neural networks

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1. Deep learning for autosegmentation for radiotherapy treatment planning: State-of-the-art and novel perspectives;Strahlentherapie und Onkologie;2024-08-06

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

3. Gaussian filter facilitated deep learning-based architecture for accurate and efficient liver tumor segmentation for radiation therapy;Frontiers in Oncology;2024-06-20

4. Review of Deep Learning Based Autosegmentation for Clinical Target Volume: Current Status and Future Directions;Advances in Radiation Oncology;2024-05

5. Reliable Delineation of Clinical Target Volumes for Cervical Cancer Radiotherapy on CT/MR Dual-Modality Images;Journal of Imaging Informatics in Medicine;2024-01-10

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