3D Contrast Image Reconstruction From Human Brain Activity

被引:6
|
作者
Zheng, Hongna [1 ]
Yao, Li [1 ]
Chen, Maoming [2 ,3 ]
Long, Zhiying [2 ,3 ]
机构
[1] Beijing Normal Univ, Sch Artificial Intelligence, Beijing 100875, Peoples R China
[2] Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing 100875, Peoples R China
[3] Beijing Normal Univ, IDG McGovern Inst Brain Res, Beijing 100875, Peoples R China
基金
中国国家自然科学基金;
关键词
Visualization; Three-dimensional displays; Image reconstruction; Decoding; Shape; Brain modeling; Functional magnetic resonance imaging; 3D contrast image; reconstruction; disparity; decoding models; fMRI;
D O I
10.1109/TNSRE.2020.3035818
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Several studies demonstrated that functional magnetic resonance imaging (fMRI) signals in early visual cortex can be used to reconstruct 2-dimensional (2D) visual contents. However, it remains unknown how to reconstruct 3-dimensional (3D) visual stimuli from fMRI signals in visual cortex. 3D visual stimuli contain 2D visual features and depth information. Moreover, binocular disparity is an important cue for depth perception. Thus, it is more challenging to reconstruct 3D visual stimuli than 2D visual stimuli from the fMRI signals of visual cortex. This study aimed to reconstruct 3D visual images by constructing three decoding models: contrast-decoding, disparity-decoding and contrast-disparity-decoding models, and testing these models with fMRI data from humans viewing 3D contrast images. The results revealed that the 3D contrast stimuli can be reconstructed from the visual cortex. And the early visual regions (V1, V2) showed predominant advantages in reconstructing the contrast in 3D images for the contrast-decoding model. The dorsal visual regions (V3A, V7 and MT) showed predominant advantages in decoding the disparity in 3D images for the disparity-decoding model. The combination of the early and dorsal visual regions showed predominant advantages in decoding both the contrast and disparity for the contrast-disparity-decoding model. The results suggested that the contrast and disparity in 3D images were mainly represented in the early and dorsal visual regions separately. The two visual systems may interact with each other to decode 3D-contrast images.
引用
收藏
页码:2699 / 2710
页数:12
相关论文
共 50 条
  • [1] A 3D RECONSTRUCTION OF THE HUMAN JAW FROM A SINGLE IMAGE
    Abdelrahim, Aly
    Shalaby, Ahmed
    Elhabian, Shireen
    Graham, James
    Farag, Aly
    2013 20TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP 2013), 2013, : 3622 - 3626
  • [2] DeepHuman: 3D Human Reconstruction From a Single Image
    Zheng, Zerong
    Yu, Tao
    Wei, Yixuan
    Dai, Qionghai
    Liu, Yebin
    2019 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2019), 2019, : 7738 - 7748
  • [3] Reconstruction of 3D Images from Human Activity by a Compound Reconstruction Model
    Hongna Zheng
    Li Yao
    Zhiying Long
    Cognitive Computation, 2022, 14 : 1509 - 1525
  • [4] Reconstruction of 3D Images from Human Activity by a Compound Reconstruction Model
    Zheng, Hongna
    Yao, Li
    Long, Zhiying
    COGNITIVE COMPUTATION, 2022, 14 (04) : 1509 - 1525
  • [5] 3D Reconstruction of Human Motion from Monocular Image Sequences
    Wandt, Bastian
    Ackermann, Hanno
    Rosenhahn, Bodo
    IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2016, 38 (08) : 1505 - 1516
  • [6] 3D human skeleton reconstruction from motion image sequence
    Zhuang, Yue-Ting
    Liu, Xiao-Ming
    Pan, Yun-He
    Yang, Jun
    Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design & Computer Graphics, 2000, 12 (04): : 245 - 250
  • [7] Complete 3D Human Reconstruction from a Single Incomplete Image
    Wang, Junying
    Yoon, Jae Shin
    Wang, Tuanfeng Y.
    Singh, Krishna Kumar
    Neumann, Ulrich
    2023 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2023, : 8748 - 8758
  • [8] 3D Human Reconstruction from an Image for Mobile Telepresence Systems
    Takeda, Yuki
    Matsuda, Akira
    Rekimoto, Jun
    2020 IEEE CONFERENCE ON VIRTUAL REALITY AND 3D USER INTERFACES WORKSHOPS (VRW 2020), 2020, : 773 - 774
  • [9] Deep image reconstruction from human brain activity
    Shen, Guohua
    Horikawa, Tomoyasu
    Majima, Kei
    Kamitani, Yukiyasu
    PLOS COMPUTATIONAL BIOLOGY, 2019, 15 (01)
  • [10] 3D Reconstruction from Plenoptic Image
    Murgia, Francesca
    Giusto, Daniele
    Perra, Cristian
    2015 23RD TELECOMMUNICATIONS FORUM TELFOR (TELFOR), 2015, : 448 - 451