Automatic 3D Point Set Reconstruction from Stereo Laparoscopic Images using Deep Neural Networks

被引：2
作者：
Antal, Balint [1 ]
机构：
[1] Univ Debrecen, Fac Informat, Debrecen, Hungary
来源：
PECCS: PROCEEDINGS OF THE 6TH INTERNATIONAL JOINT CONFERENCE ON PERVASIVE AND EMBEDDED COMPUTING AND COMMUNICATION SYSTEMS | 2016年
关键词：
Endoscope; Laparoscope; Heart; 3D Reconstruction; Depth Map; Deep Neural Networks; Machine Learning;
D O I：
10.5220/0006008001160121
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper, an automatic approach to predict 3D coordinates from stereo laparoscopic images is presented. The approach maps a vector of pixel intensities to 3D coordinates through training a six layer deep neural network. The architectural aspects of the approach is presented and in detail and the method is evaluated on a publicly available dataset with promising results.
引用
收藏
页码：116 / 121
页数：6
相关论文
共 13 条
  • [1] Bastien F., 2012, Theano: new features and speed improvements
  • [2] Bergstra J., 2010, P PHTH SCI COMP C SC
  • [3] Chollet Francois., 2015, Keras
  • [4] Glorot X., 2010, P 13 INT C ART INT S, P249, DOI DOI 10.1109/LGRS.2016.2565705
  • [5] Glorot X., 2011, P 14 INT C ARTIFICIA, P315
  • [6] RIDGE REGRESSION - BIASED ESTIMATION FOR NONORTHOGONAL PROBLEMS
    HOERL, AE
    KENNARD, RW
    [J]. TECHNOMETRICS, 1970, 12 (01) : 55 - &
  • [7] Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery
    Maier-Hein, L.
    Mountney, P.
    Bartoli, A.
    Elhawary, H.
    Elson, D.
    Groch, A.
    Kolb, A.
    Rodrigues, M.
    Sorger, J.
    Speidel, S.
    Stoyanov, D.
    [J]. MEDICAL IMAGE ANALYSIS, 2013, 17 (08) : 974 - 996
  • [8] Nair V., 2010, PROC INT C MACH LEAR, P807, DOI DOI 10.5555/3104322.3104425
  • [9] Pratt P, 2010, LECT NOTES COMPUT SC, V6361, P77
  • [10] Deep learning
    Rusk, Nicole
    [J]. NATURE METHODS, 2016, 13 (01) : 35 - 35
12