Journals Articles Conferences News About CLP
Submit a paper Email Alert
Search
Search
Articles
Journals
News
Advanced Search
Top Searches
2D MaterialsTransformation opticsQuantum PhotonicsSmall lasersSemiconductor UV PhotonicsSupersymmetric microring laser arrays

Chinese Journal of Lasers, Volume. 49, Issue 20, 2007302(2022)

Spatial Registration Method for Neuronavigation Using Adaptive Thresholds

Cong Chen1, Miao Liu1、*, Jigang Wang2, and Shourui Yang3
Author Affiliations
  • 1Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China
  • 2Tianjin Haihe Hospital, Tianjin 300222, China
  • 3School of Computer Science and Engineering, Tianjin University of Technology, Tianjin 300384, China
    • show less
    AbstractGet PDF(in Chinese)
    Figures&Tables (17)
    Equations (0)
    References (15)
    Tools
    Paper Information
    Topics
    Figures & Tables(17)
    Flow chart of adaptive threshold registration method

    Fig. 1. Flow chart of adaptive threshold registration method

    Download full size
    Schematic of binocular stereo vision

    Fig. 2. Schematic of binocular stereo vision

    Download full size
    Picture of face point cloud collection system

    Fig. 3. Picture of face point cloud collection system

    Download full size
    Calculation diagram of fast point feature histogram (FPFH)

    Fig. 4. Calculation diagram of fast point feature histogram (FPFH)

    Download full size
    Head model

    Fig. 5. Head model

    Download full size
    Target balls and their labels

    Fig. 6. Target balls and their labels

    Download full size
    Three-dimensional reconstruction result of CT images. (a) Point cloud of face；(b) point cloud of target balls

    Fig. 7. Three-dimensional reconstruction result of CT images. (a) Point cloud of face；(b) point cloud of target balls

    Download full size
    Point clouds of face in CT and world coordinate system. (a) CT point cloud; (b) point cloud 0; (c) point cloud 1; (d) point cloud 2; (e) point cloud 3

    Fig. 8. Point clouds of face in CT and world coordinate system. (a) CT point cloud; (b) point cloud 0; (c) point cloud 1; (d) point cloud 2; (e) point cloud 3

    Download full size
    Point clouds of face after downsampling. (a) CT point cloud; (b) point cloud 0; (c) point cloud 1; (d) point cloud 2; (e) point cloud 3

    Fig. 9. Point clouds of face after downsampling. (a) CT point cloud; (b) point cloud 0; (c) point cloud 1; (d) point cloud 2; (e) point cloud 3

    Download full size
    Residual distributions of coarse registration. (a) No deformation; (b) deformation 1; (c) deformation 2; (d) deformation 3

    Fig. 10. Residual distributions of coarse registration. (a) No deformation; (b) deformation 1; (c) deformation 2; (d) deformation 3

    Download full size
    Counts of each points excluded. (a) No deformation; (b) deformation 1; (c) deformation 2; (d) deformation 3

    Fig. 11. Counts of each points excluded. (a) No deformation; (b) deformation 1; (c) deformation 2; (d) deformation 3

    Download full size
    Residual distribution of fine registration of general ICP method. (a) No deformation; (b) deformation 1;

    Fig. 12. Residual distribution of fine registration of general ICP method. (a) No deformation; (b) deformation 1;

    Download full size
    Residual distribution of fine registration of our method. (a) No deformation; (b) deformation 1; (c) deformation 2; (d) deformation 3

    Fig. 13. Residual distribution of fine registration of our method. (a) No deformation; (b) deformation 1; (c) deformation 2; (d) deformation 3

    Download full size
    Box plot of mean registration error of two methods

    Fig. 14. Box plot of mean registration error of two methods

    Download full size

    • Table 1. Transformation parameter range of coarse registration

      View table

      Table 1. Transformation parameter range of coarse registration

      ConditionTx/mmTy/mmTz/mm
      No deformation－161.94 to －148.02－621.58 to －614.03－13.27 to 6.82
      Deformation 1－162.86 to －146.08－621.93 to －612.69－25.51 to 15.32
      Deformation 2－174.79 to －134.04－627.82 to －607.69－16.04 to 9.02
      Deformation 3－158.32 to －136.13－644.67 to －635.54－93.69 to －65.00

    • Table 2. Target registration error of our method

      View table

      Table 2. Target registration error of our method

      Target labelError /mm
      No deformationDeformation 1Deformation 2Deformation 3
      10.75±0.050.34±0.120.33±0.100.67±0.16
      20.60±0.040.37±0.110.25±0.040.56±0.20
      30.67±0.030.32±0.080.29±0.060.61±0.13
      40.58±0.030.44±0.060.23±0.030.63±0.17
      50.54±0.030.34±0.070.28±0.040.51±0.18
      60.45±0.030.35±0.050.23±0.050.50±0.17
      70.68±0.030.32±0.060.19±0.030.71±0.10
      80.53±0.040.25±0.080.27±0.040.64±0.13
      110.57±0.050.37±0.120.29±0.060.65±0.15
      120.43±0.060.32±0.130.35±0.080.60±0.14
      130.40±0.050.27±0.070.24±0.090.57±0.11
      140.52±0.070.29±0.140.26±0.060.26±0.20
      150.48±0.070.42±0.170.41±0.070.38±0.14
      Mean value0.55±0.050.34±0.100.28±0.060.56±0.15

    • Table 3. Target registration error of general ICP method

      View table

      Table 3. Target registration error of general ICP method

      Target labelError /mm
      No deformationDeformation 1Deformation 2Deformation 3
      10.74±0.051.81±0.052.64±0.050.96±0.11
      20.60±0.041.66±0.052.41±0.050.56±0.14
      30.67±0.031.97±0.043.02±0.030.95±0.24
      40.57±0.031.83±0.042.65±0.030.66±0.07
      50.53±0.031.65±0.042.43±0.030.65±0.08
      60.45±0.031.58±0.042.22±0.030.64±0.11
      70.68±0.032.06±0.032.98±0.031.13±0.21
      80.53±0.031.89±0.032.68±0.030.84±0.15
      110.57±0.041.87±0.032.67±0.041.09±0.07
      120.41±0.051.72±0.042.53±0.041.16±0.10
      130.39±0.041.77±0.052.17±0.051.15±0.09
      140.50±0.061.96±0.082.76±0.061.71±0.08
      150.47±0.061.77±0.072.55±0.061.64±0.09
      Mean value0.55±0.041.81±0.052.59±0.041.01±0.12
    Tools

    Get Citation

    Copy Citation Text

    Cong Chen, Miao Liu, Jigang Wang, Shourui Yang. Spatial Registration Method for Neuronavigation Using Adaptive Thresholds[J]. Chinese Journal of Lasers, 2022, 49(20): 2007302

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Set citation alerts for article
    Save article for my favorites
    Paper Information

    Category: Neurophotonics and Optical Regulation

    Received: May. 7, 2022

    Accepted: May. 27, 2022

    Published Online: Aug. 10, 2022

    The Author Email: Liu Miao (3005202010@tju.edu.cn)

    DOI:10.3788/CJL202249.2007302

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology