Feasibility study on automatic segmentation of pelvic intestinal tube for radiotherapy images based on deep learning

Yu-jie ZHANG, Xu YUAN, Han XIAO, Jian-ying ZHANG

Fudan University Journal of Medical Sciences ›› 2024, Vol. 51 ›› Issue (02) : 243-248.

PDF(1033 KB)
Welcome to visit Fudan University Journal of Medical Sciences, Share:
PDF(1033 KB)
Fudan University Journal of Medical Sciences ›› 2024, Vol. 51 ›› Issue (02) : 243-248. DOI: 10.3969/j.issn.1672-8467.2024.02.015
Methods and Techniques

Feasibility study on automatic segmentation of pelvic intestinal tube for radiotherapy images based on deep learning

    {{javascript:window.custom_author_en_index=0;}}
  • {{article.zuoZhe_EN}}
Author information +
History +

HeighLight

{{article.keyPoints_en}}

Abstract

{{article.zhaiyao_en}}

Key words

QR code of this article

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations
{{article.zuoZheEn_L}}. {{article.title_en}}[J]. {{journal.qiKanMingCheng_EN}}, 2024, 51(02): 243-248 https://doi.org/10.3969/j.issn.1672-8467.2024.02.015

References

Publishing order | Descend order by publishing year | Descend order by cited within

References

{{article.reference}}

Funding

RIGHTS & PERMISSIONS

{{article.copyrightStatement_en}}
{{article.copyrightLicense_en}}
PDF(1033 KB)

Accesses

Citation

Detail
Sections
Recommended
Total visitors:　 Visitors of today: 　 Now online:
Copyright © Fudan University Journal of Medical Sciences, All Rights Reserved.
Powered by Beijing Magtech Co. Ltd,.

/

〈 〉