Comparison of two-dimensional and three-dimensional U-Net architectures for segmentation of adipose tissue in cardiac magnetic resonance images

被引:0
|
作者
Kulasekara, Michaela [1 ]
Dinh, Vu Quang [1 ]
Fernandez-del-Valle, Maria [2 ,3 ]
Klingensmith, Jon D. [1 ]
机构
[1] Department of Electrical and Computer Engineering, Southern Illinois University Edwardsville, Box 1801, Edwardsville,IL,62026, United States
[2] Department of Functional Biology, University of Oviedo, Oviedo, Spain
[3] Health Research Institute of the Principality of Asturias (ISPA), Asturias, Spain
来源
关键词
2 - Dimensional - Adipose tissue - Cardiac magnetic resonance images - Convolutional neural network - Dimensional model - Epicardial adipose tissue - NET architecture - Similarity coefficients - Two-dimensional - Volumetrics;
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
页码:2291 / 2306
相关论文
共 50 条
  • [31] Identification of the Facial Colliculus in Two-dimensional and Three-dimensional Images
    Uchida, Tatsuya
    Kin, Taichi
    Koike, Tsukasa
    Kiyofuji, Satoshi
    Uchikawa, Hiroki
    Takeda, Yasuhiro
    Miyawaki, Satoru
    Nakatomi, Hirofumi
    Saito, Nobuhito
    NEUROLOGIA MEDICO-CHIRURGICA, 2021, 61 (06) : 376 - 384
  • [32] Learning to perceive three-dimensional shapes in two-dimensional images
    Sinha, P.
    PERCEPTION, 1995, 24 : 4 - 5
  • [33] Enhanced three-dimensional U-Net with graph-based refining for segmentation of gastrointestinal stromal tumours
    Wang, Qiong
    Li, Zhipeng
    Zhao, Wanqing
    Wu, Hao
    Xie, Fei
    Guan, Ziyu
    Zhao, Wei
    IET COMPUTER VISION, 2021, 15 (08) : 549 - 560
  • [34] Recognizing three-dimensional objects by comparing two-dimensional images
    Huttenlocher, DP
    Lorigo, LM
    1996 IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, PROCEEDINGS, 1996, : 878 - 884
  • [35] Deconvolving two-dimensional images of three-dimensional momentum trajectories
    Zhao, K
    Colvin, T
    Hill, WT
    Zhang, G
    REVIEW OF SCIENTIFIC INSTRUMENTS, 2002, 73 (08): : 3044 - 3050
  • [36] RSU-Net: U-net based on residual and self-attention mechanism in the segmentation of cardiac magnetic resonance images
    Li, Yuan-Zhe
    Wang, Yi
    Huang, Yin-Hui
    Xiang, Ping
    Liu, Wen-Xi
    Lai, Qing-Quan
    Gao, Yi-Yuan
    Xu, Mao-Sheng
    Guo, Yi-Fan
    COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2023, 231
  • [37] Automatic needle segmentation in three-dimensional ultrasound images using two orthogonal two-dimensional image projections
    Ding, MY
    Cardinal, HN
    Fenster, A
    MEDICAL PHYSICS, 2003, 30 (02) : 222 - 234
  • [38] Deep-learning-based automatic facial bone segmentation using a two-dimensional U-Net
    Morita, D.
    Mazen, S.
    Tsujiko, S.
    Otake, Y.
    Sato, Y.
    Numajiri, T.
    INTERNATIONAL JOURNAL OF ORAL AND MAXILLOFACIAL SURGERY, 2023, 52 (07) : 787 - 792
  • [39] Comparison of two-dimensional and three-dimensional iterative watershed segmentation methods in hepatic tumor volumetrics
    Ray, Shonket
    Hagge, Rosalie
    Gillen, Marijo
    Cerejo, Miguel
    Shakeri, Shidrokh
    Beckett, Laurel
    Greasby, Tamara
    Badawi, Ramsey D.
    MEDICAL PHYSICS, 2008, 35 (12) : 5869 - 5881
  • [40] Three- and four-dimensional reconstruction of intra-cardiac anatomy from two-dimensional magnetic resonance images
    Miquel, ME
    Hill, DLG
    Baker, EJ
    Qureshi, SA
    Simon, RDB
    Keevil, SF
    Razavi, RS
    INTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING, 2003, 19 (03): : 239 - 254