FRNET: An Effective Hybrid Structure for Automatic Segmentation of Head and Neck Primary Tumors from Multimodal Images

LiuQiangShiJunQiaoLiangZhuZiqi

医学影像与智能诊断方向论文：FRNET: An Effective Hybrid Structure for Automatic Segmentation of Head

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内容导读Reading note

分类与摘要Category & abstract

聚焦医学影像分割、诊断或数据选择，体现 AI 方法在临床相关任务中的应用。

Metadata

完整论文信息Full record

title: FRNET: An Effective Hybrid Structure for Automatic Segmentation of Head and Neck Primary Tumors from Multimodal Images
title_zh: 待补充
abstract: 待补充
abstract_zh: 待补充
keywords: Medical, 学位认定 C, CCF C
year: 2023
published_date: 待补充
online_date: 待补充
paper_type: Conference
publication_status: Published
volume: 待补充
issue: 待补充
pages: 待补充
article_number: 待补充
publisher: IEEE
doi: 10.1109/isbi53787.2023.10230383
research_area: 医学影像与智能诊断
tags: Medical, 学位认定 C, CCF C
category: 医学影像与智能诊断
summary: 聚焦医学影像分割、诊断或数据选择，体现 AI 方法在临床相关任务中的应用。
authors: Liu, Qiang, Shi, Jun, Qiao, Liang, Zhu, Ziqi
corresponding_authors: 待补充
affiliations: 待补充
funding: 待补充

Research area

医学影像与智能诊断

Citation

Liu, Qiang; Shi, Jun; Qiao, Liang; Zhu, Ziqi; An, Hong; Zhao, Minfan, FRNET: An Effective Hybrid Structure for Automatic Segmentation of Head and Neck Primary Tumors from Multimodal Images, In the Proceedings of 20th IEEE International Symposium on Biomedical Imaging (ISBI 23),Cartagena, Colombia, April 18, 2023 - April 21, 2023.

BibTeX

@article{acsa2023_42,
  title = {FRNET: An Effective Hybrid Structure for Automatic Segmentation of Head and Neck Primary Tumors from Multimodal Images},
  year = {2023},
  doi = {10.1109/isbi53787.2023.10230383}
}