GPU-accelerated ray-casting for 3D fiber orientation analysis

被引:2
|
作者
Shkarin, Roman [1 ,2 ]
Shkarina, Svetlana [3 ,4 ]
Weinhardt, Venera [1 ,4 ,5 ]
Surmenev, Roman A. [3 ]
Surmeneva, Maria A. [3 ]
Shkarin, Andrei [1 ]
Baumbach, Tilo [1 ,4 ]
Mikut, Ralf [2 ]
机构
[1] Karlsruhe Inst Technol, Lab Applicat Synchrotron Radiat, Karlsruhe, Germany
[2] Karlsruhe Inst Technol, Inst Automat & Appl Comp Sci, Karlsruhe, Germany
[3] Natl Res Tomsk Polytech Univ, Res Sch Chem & Appl Biomed Sci, Phys Mat Sci & Composite Mat Ctr, Tomsk, Russia
[4] Karlsruhe Inst Technol, Inst Photon Sci & Synchrotron Radiat, Eggenstein Leopoldshafen, Germany
[5] Heidelberg Univ, Ctr Organismal Studies, COS, Heidelberg, Germany
来源
PLOS ONE | 2020年 / 15卷 / 07期
关键词
AUTOMATED MEASUREMENT; FOURIER-ANALYSIS; ALIGNMENT; COMPOSITES; QUANTIFICATION; ORGANIZATION; TOMOGRAPHY; MORPHOLOGY; ALGORITHM; MODELS;
D O I
10.1371/journal.pone.0236420
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Orientation analysis of fibers is widely applied in the fields of medical, material and life sciences. The orientation information allows predicting properties and behavior of materials to validate and guide a fabrication process of materials with controlled fiber orientation. Meanwhile, development of detector systems for high-resolution non-invasive 3D imaging techniques led to a significant increase in the amount of generated data per a sample up to dozens of gigabytes. Though plenty of 3D orientation estimation algorithms were developed in recent years, neither of them can process large datasets in a reasonable amount of time. This fact complicates the further analysis and makes impossible fast feedback to adjust fabrication parameters. In this work, we present a new method for quantifying the 3D orientation of fibers. The GPU implementation of the proposed method surpasses another popular method for 3D orientation analysis regarding accuracy and speed. The validation of both methods was performed on a synthetic dataset with varying parameters of fibers. Moreover, the proposed method was applied to perform orientation analysis of scaffolds with different fibrous micro-architecture studied with the synchrotron mu CT imaging setup. Each acquired dataset of size 600x600x450 voxels was analyzed in less 2 minutes using standard PC equipped with a single GPU.
引用
收藏
页数:16
相关论文
共 50 条
  • [1] A Framework for 3D X-Ray CT Iterative Reconstruction Using GPU-accelerated Ray Casting
    Zhang, Zhan
    Ghadai, Sambit
    Bingol, Onur Rauf
    Krishnamurthy, Adarsh
    Bond, Leonard J.
    45TH ANNUAL REVIEW OF PROGRESS IN QUANTITATIVE NONDESTRUCTIVE EVALUATION, VOL 38, 2019, 2102
  • [2] GPU-Accelerated Octree Encoding Ray Casting Algorithm
    Liu, Bai-lin
    Chen, Guo-yi
    INTERNATIONAL CONFERENCE ON ENERGY, ENVIRONMENT AND MATERIALS ENGINEERING (EEME 2014), 2014, : 906 - 910
  • [3] GPU-Accelerated 3D Normal Distributions Transform
    Nguyen, Anh
    Cano, Abraham Monrroy
    Edahiro, Masato
    Kato, Shinpei
    JOURNAL OF ROBOTICS AND MECHATRONICS, 2023, 35 (02) : 445 - 459
  • [4] GPU-accelerated feature tracking for 3D reconstruction
    Cao, Mingwei
    Jia, Wei
    Li, Shujie
    Li, Yujie
    Zheng, Liping
    Liu, Xiaoping
    OPTICS AND LASER TECHNOLOGY, 2019, 110 (165-175): : 165 - 175
  • [5] GPU-accelerated Parallel 3D Image Thinning
    Hu, Bingfeng
    Yang, Xuan
    2013 IEEE 15TH INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING AND COMMUNICATIONS & 2013 IEEE INTERNATIONAL CONFERENCE ON EMBEDDED AND UBIQUITOUS COMPUTING (HPCC_EUC), 2013, : 149 - 152
  • [6] A GPU-Accelerated TLSPH Algorithm for 3D Geometrical Nonlinear Structural Analysis
    He, Jiandong
    Lei, Juanmian
    INTERNATIONAL JOURNAL OF COMPUTATIONAL METHODS, 2019, 16 (07)
  • [7] GPU-Accelerated Nearest Neighbor Search for 3D Registration
    Qiu, Deyuan
    May, Stefan
    Nuechter, Andreas
    COMPUTER VISION SYSTEMS, PROCEEDINGS, 2009, 5815 : 194 - +
  • [8] GPU-accelerated denoising of 3D magnetic resonance images
    Howison, Mark
    Bethel, E. Wes
    JOURNAL OF REAL-TIME IMAGE PROCESSING, 2017, 13 (04) : 713 - 724
  • [9] GPU-accelerated denoising of 3D magnetic resonance images
    Mark Howison
    E. Wes Bethel
    Journal of Real-Time Image Processing, 2017, 13 : 713 - 724
  • [10] GPU-Accelerated Tracking of the Motion of 3D Articulated Figure
    Krzeszowski, Tomasz
    Kwolek, Bogdan
    Wojciechowski, Konrad
    COMPUTER VISION AND GRAPHICS, PT I, 2010, 6374 : 155 - 162