A transformer-based multi-task deep learning model for simultaneous infiltrated brain area identification and segmentation of gliomas

被引:0
|
作者
Yin Li
Kaiyi Zheng
Shuang Li
Yongju Yi
Min Li
Yufan Ren
Congyue Guo
Liming Zhong
Wei Yang
Xinming Li
Lin Yao
机构
[1] The Sixth Affiliated Hospital,Department of Information
[2] Sun Yat-Sen University,School of Biomedical Engineering
[3] Southern Medical University,Department of General Practice
[4] Guangdong Provincial Key Laboratory of Medical Image Processing,Department of Radiology
[5] The Sixth Affiliated Hospital,undefined
[6] Sun Yat-Sen University,undefined
[7] Zhujiang Hospital,undefined
[8] Southern Medical University,undefined
来源
关键词
Glioma; Deep learning; Tumor segmentation; Brain area Identification; Multi-task;
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
相关论文
共 50 条
  • [1] A transformer-based multi-task deep learning model for simultaneous infiltrated brain area identification and segmentation of gliomas
    Li, Yin
    Zheng, Kaiyi
    Li, Shuang
    Yi, Yongju
    Li, Min
    Ren, Yufan
    Guo, Congyue
    Zhong, Liming
    Yang, Wei
    Li, Xinming
    Yao, Lin
    CANCER IMAGING, 2023, 23 (01)
  • [2] A transformer-based multi-task deep learning model for simultaneous T-stage identification and segmentation of nasopharyngeal carcinoma
    Yang, Kaifan
    Dong, Xiuyu
    Tang, Fan
    Ye, Feng
    Chen, Bei
    Liang, Shujun
    Zhang, Yu
    Xu, Yikai
    FRONTIERS IN ONCOLOGY, 2024, 14
  • [3] Transformer-based multi-task learning for classification and segmentation of gastrointestinal tract endoscopic images
    Tang, Suigu
    Yu, Xiaoyuan
    Cheang, Chak Fong
    Liang, Yanyan
    Zhao, Penghui
    Yu, Hon Ho
    Choi, I. Cheong
    COMPUTERS IN BIOLOGY AND MEDICINE, 2023, 157
  • [4] A Deep Multi-Task Learning Framework for Brain Tumor Segmentation
    Huang, He
    Yang, Guang
    Zhang, Wenbo
    Xu, Xiaomei
    Yang, Weiji
    Jiang, Weiwei
    Lai, Xiaobo
    FRONTIERS IN ONCOLOGY, 2021, 11
  • [5] Predicting Outcomes for Cancer Patients with Transformer-Based Multi-task Learning
    Gerrard, Leah
    Peng, Xueping
    Clarke, Allison
    Schlegel, Clement
    Jiang, Jing
    AI 2021: ADVANCES IN ARTIFICIAL INTELLIGENCE, 2022, 13151 : 381 - 392
  • [6] MFUnetr: A transformer-based multi-task learning network for multi-organ segmentation from partially labeled datasets
    Hao, Qin
    Tian, Shengwei
    Yu, Long
    Wang, Junwen
    BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2023, 85
  • [7] Multi-task Active Learning for Pre-trained Transformer-based Models
    Rotman, Guy
    Reichart, Roi
    TRANSACTIONS OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, 2022, 10 : 1209 - 1228
  • [8] HTML']HTML: Hierarchical Transformer-based Multi-task Learning for Volatility Prediction
    Yang, Linyi
    Ng, Tin Lok James
    Smyth, Barry
    Dong, Riuhai
    WEB CONFERENCE 2020: PROCEEDINGS OF THE WORLD WIDE WEB CONFERENCE (WWW 2020), 2020, : 441 - 451
  • [9] Multi-task Learning for Brain Tumor Segmentation
    Weninger, Leon
    Liu, Qianyu
    Merhof, Dorit
    BRAINLESION: GLIOMA, MULTIPLE SCLEROSIS, STROKE AND TRAUMATIC BRAIN INJURIES (BRAINLES 2019), PT I, 2020, 11992 : 327 - 337
  • [10] A multi-task deep learning model for EGFR genotyping prediction and GTV segmentation of brain metastasis
    Zichun Zhou
    Min Wang
    Rubin Zhao
    Yan Shao
    Ligang Xing
    Qingtao Qiu
    Yong Yin
    Journal of Translational Medicine, 21