AUTOMATIC CO-REGISTRATION OF MEG AND 3D DIGITIZATION USING 3D GENERALIZED HOUGH TRANSFORM

被引:1
|
作者
Lin, Sheng-Kai [1 ]
Lo, Rong-Chin [1 ]
Lee, Ren-Guey [1 ]
机构
[1] Natl Taipei Univ Technol, Inst Elect Engn, 1,Sec 3,Zhongxiao E Rd, Taipei 10608, Taiwan
关键词
Co-registration; Magnetoencephalography; Third dimension digitizer; 3D generalized Hough transform; CURVES; INVARIANT;
D O I
10.4015/S1016237220500192
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
In this study, we propose a new automatic co-registration method for the coordinate systems of magnetoencephalography (MEG) data and third dimension digitizer (3D DIG) data of a head using the 3D generalized Hough transform (GHT) during image processing. The technique is important for the research of brain functionalities; it can be done automatically, and quickly combines data from functional brain mapping tools like MEG and DIG, etc. MEG is a measurement instrument used to noninvasively analyze the physiological activity of neurons with high temporal resolution, but it lacks the head-shape of subjects and head with respect to the MEG sensors. 3D DIG can record head-shape, facial features, and anatomical markers in a 3D coordinate system in real time. Thus, combining the two modalities is beneficial in correlating the obtained brain data with physiological activity. According to much of the research, the GHT is useful for recognizing or locating two 2D images. However, the GHT algorithm can be extended to the 3D GHT to automatically co-register the 3D data. In this study, we use the 3D GHT to co-register three subject datasets with MEG and 3D DIG data, and evaluate the average distance errors between the proposed method and the MEG160 system. Some of the experimental results demonstrate the applicability of the proposed 3D GHT accurately and efficiently.
引用
收藏
页数:7
相关论文
共 50 条
  • [1] MEG and 3D Digitization Co-registration of Head Using 3D Hough Transform
    Lin, Sheng Kai
    Lo, Rong Chin
    [J]. INTERNATIONAL CONFERENCE ON BIOLOGICAL, MEDICAL AND CHEMICAL ENGINEERING (BMCE 2013), 2013, : 653 - 656
  • [2] MEG-MRI CO-REGISTRATION USING 3D GENERALIZED HOUGH TRANSFORM
    Lin, Sheng-Kai
    Lo, Rong-Chin
    Lee, Ren-Guey
    [J]. BIOMEDICAL ENGINEERING-APPLICATIONS BASIS COMMUNICATIONS, 2020, 32 (04):
  • [3] MAGNETOENCEPHALOGRAPHY-ELECTROENCEPHALOGRAPHY CO-REGISTRATION USING 3D GENERALIZED HOUGH TRANSFORM
    Lin, Sheng-Kai
    Lo, Rong-Chin
    Lee, Ren-Guey
    [J]. BIOMEDICAL ENGINEERING-APPLICATIONS BASIS COMMUNICATIONS, 2020, 32 (03):
  • [4] Automatic co-registration of OPM-MEG and MRI using a 3D laser scanner
    Gao, Zhenfeng
    Cao, Fuzhi
    An, Nan
    Ning, Xiaolin
    [J]. MEASUREMENT, 2023, 223
  • [5] Automatic 3D Surface Co-Registration Using Keypoint Matching
    Persad, Ravi Ancil
    Armenakis, Costas
    [J]. PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, 2017, 83 (02): : 137 - 151
  • [6] Automatic needle segmentation in 3D ultrasound images using 3D Hough transform
    Zhou, Hua
    Qiu, Wu
    Ding, Mingyue
    Zhang, Songgeng
    [J]. MIPPR 2007: MEDICAL IMAGING, PARALLEL PROCESSING OF IMAGES, AND OPTIMIZATION TECHNIQUES, 2007, 6789
  • [7] Automatic needle segmentation in 3D ultrasound images using 3D improved hough transform
    Zhou, Hua
    Qiu, Wu
    Ding, Mingyue
    Zhang, Songgen
    [J]. MEDICAL IMAGING 2008: VISUALIZATION, IMAGE-GUIDED PROCEDURES, AND MODELING, PTS 1 AND 2, 2008, 6918
  • [8] Demisting the Hough Transform for 3D Shape Recognition and Registration
    Oliver J. Woodford
    Minh-Tri Pham
    Atsuto Maki
    Frank Perbet
    Björn Stenger
    [J]. International Journal of Computer Vision, 2014, 106 : 332 - 341
  • [9] Demisting the Hough Transform for 3D Shape Recognition and Registration
    Woodford, Oliver J.
    Minh-Tri Pham
    Maki, Atsuto
    Perbet, Frank
    Stenger, Bjoern
    [J]. INTERNATIONAL JOURNAL OF COMPUTER VISION, 2014, 106 (03) : 332 - 341
  • [10] Demisting the Hough Transform for 3D Shape Recognition and Registration
    Woodford, Oliver J.
    Minh-Tri Pham
    Maki, Atsuto
    Perbet, Frank
    Stenger, Bjoern
    [J]. PROCEEDINGS OF THE BRITISH MACHINE VISION CONFERENCE 2011, 2011,