Regularizing Iterative Reconstruction with Deep Neural Networks

被引：0
|
作者：
Ozaki, S. [1 ]
Kaji, S. [2 ]
Haga, A. [3 ]
Nawa, K. [1 ]
Ohta, T. [1 ]
Nozawa, Y. [1 ]
Nakamoto, T. [1 ]
Imae, T. [1 ]
Nakagawa, K. [1 ]
机构：
[1] Univ Tokyo Hosp, Tokyo, Japan
[2] Kyushu Univ, Inst Math Ind, Kyushu, Japan
[3] Tokushima Univ, Tokushima, Japan
来源：
MEDICAL PHYSICS | 2020年 / 47卷 / 06期
关键词：
D O I：
暂无
中图分类号：
R8 [特种医学]; R445 [影像诊断学];
学科分类号：
1002 ; 100207 ; 1009 ;
摘要：
BReP-SNAP-
引用
收藏
页码：E437 / E438
页数：2
相关论文
共 50 条
  • [21] Regularizing Activation Distribution for Training Binarized Deep Networks
    Ding, Ruizhou
    Chin, Ting-Wu
    Liu, Zeye
    Marculescu, Diana
    2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2019), 2019, : 11400 - 11409
  • [22] Systematic evaluation of iterative deep neural networks for fast parallel MRI reconstruction with sensitivity-weighted coil combination
    Hammernik, Kerstin
    Schlemper, Jo
    Qin, Chen
    Duan, Jinming
    Summers, Ronald M.
    Rueckert, Daniel
    MAGNETIC RESONANCE IN MEDICINE, 2021, 86 (04) : 1859 - 1872
  • [23] Regularizing Neural Networks via Retaining Confident Connections
    Zhang, Shengnan
    Hou, Yuexian
    Wang, Benyou
    Song, Dawei
    ENTROPY, 2017, 19 (07)
  • [24] Regularizing Deep Networks by Modeling and Predicting Label Structure
    Mostajabi, Mohammadreza
    Maire, Michael
    Shakhnarovich, Gregory
    2018 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2018, : 5629 - 5638
  • [25] Regularizing Neural Networks via Adversarial Model Perturbation
    Zheng, Yaowei
    Zhang, Richong
    Mao, Yongyi
    2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, CVPR 2021, 2021, : 8152 - 8161
  • [26] Revisiting spatial dropout for regularizing convolutional neural networks
    Sanghun Lee
    Chulhee Lee
    Multimedia Tools and Applications, 2020, 79 : 34195 - 34207
  • [27] Revisiting spatial dropout for regularizing convolutional neural networks
    Lee, Sanghun
    Lee, Chulhee
    MULTIMEDIA TOOLS AND APPLICATIONS, 2020, 79 (45-46) : 34195 - 34207
  • [28] REGULARIZING NEURAL NETWORKS BY STOCHASTICALLY TRAINING LAYER ENSEMBLES
    Labach, Alex
    Valaee, Shahrokh
    PROCEEDINGS OF THE 2020 IEEE 30TH INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING (MLSP), 2020,
  • [29] Regularizing Neural Networks via Minimizing Hyperspherical Energy
    Lin, Rongmei
    Liu, Weiyang
    Liu, Zhen
    Feng, Chen
    Yu, Zhiding
    Rehg, James M.
    Xiong, Li
    Song, Le
    2020 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2020, : 6916 - 6925
  • [30] Regularizing Neural Networks via Stochastic Branch Layers
    Park, Wonpyo
    Seo, Paul Hongsuck
    Han, Bohyung
    Cho, Minsu
    ASIAN CONFERENCE ON MACHINE LEARNING, VOL 101, 2019, 101 : 678 - 693
12345