GPU-accelerated 3D mipmap for real-time visualization of ultrasound volume data

被引:5
|
作者
Kwon, Koojoo [1 ]
Lee, Eun-Seok [1 ]
Shin, Byeong-Seok [1 ]
机构
[1] Inha Univ, Dept Comp & Informat Engn, Inchon, South Korea
基金
新加坡国家研究基金会;
关键词
Ultrasound data; Volume rendering; 3D noise filtering; Mipmap; SPECKLE REDUCTION; ENHANCEMENT; NOISE;
D O I
10.1016/j.compbiomed.2013.07.014
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Ultrasound volume rendering is an efficient method for visualizing the shape of fetuses in obstetrics and gynecology. However, in order to obtain high-quality ultrasound volume rendering, noise removal and coordinates conversion are essential prerequisites. Ultrasound data needs to undergo a noise filtering process; otherwise, artifacts and speckle noise cause quality degradation in the final images. Several two-dimensional (2D) noise filtering methods have been used to reduce this noise. However, these 2D filtering methods ignore relevant information in-between adjacent 2D-scanned images. Although three-dimensional (3D) noise filtering methods are used, they require more processing time than 2D-based methods. In addition, the sampling position in the ultrasonic volume rendering process has to be transformed between conical ultrasound coordinates and Cartesian coordinates. We propose a 3D-mipmap-based noise reduction method that uses graphics hardware, as a typical 3D mipmap requires less time to be generated and less storage capacity. In our method, we compare the density values of the corresponding points on consecutive mipmap levels and find the noise area using the difference in the density values. We also provide a noise detector for adaptively selecting the mipmap level using the difference of two mipmap levels. Our method can visualize 3D ultrasound data in real time with 3D noise filtering. (c) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1382 / 1389
页数:8
相关论文
共 50 条
  • [21] GPU-accelerated Matrix-Free 3D Ultrasound Reconstruction for Nondestructive Testing
    Kirchhof, Jan
    Semper, Sebastian
    Roemer, Florian
    2018 IEEE INTERNATIONAL ULTRASONICS SYMPOSIUM (IUS), 2018,
  • [22] Real-Time Visualized Freehand 3D Ultrasound Reconstruction Based on GPU
    Dai, Yakang
    Tian, Jie
    Dong, Di
    Yan, Guorui
    Zheng, Hairong
    IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE, 2010, 14 (06): : 1338 - 1345
  • [23] GPU-accelerated Real-time Free-viewpoint DIBR for 3DTV
    Do, Luat
    Bravo, German
    Zinger, Svitlana
    de With, Peter H. N.
    IEEE TRANSACTIONS ON CONSUMER ELECTRONICS, 2012, 58 (02) : 633 - 640
  • [24] GPU-accelerated phase extraction algorithm for interferograms: A real-time application
    Zhu, Xiaoqiang
    Wu, Yongqian
    Liu, Fengwei
    OPTICAL METROLOGY AND INSPECTION FOR INDUSTRIAL APPLICATIONS IV, 2016, 10023
  • [25] GPU-Accelerated Real-Time Stereo Estimation With Binary Neural Network
    Chen, Gang
    Meng, Haitao
    Liang, Yucheng
    Huang, Kai
    IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2020, 31 (12) : 2896 - 2907
  • [26] GPU-accelerated ray-tracing for real-time treatment planning
    Heinrich, H.
    Ziegenhein, P.
    Kamerling, C. P.
    Frorning, H.
    Pelfke, U.
    XVII INTERNATIONAL CONFERENCE ON THE USE OF COMPUTERS IN RADIATION THERAPY (ICCR 2013), 2014, 489
  • [27] GPU-Accelerated Real-Time Path Planning and the Predictable Execution Model
    Forsberg, Bjorn
    Palossi, Daniele
    Marongiu, Andrea
    Benini, Luca
    INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE (ICCS 2017), 2017, 108 : 2428 - 2432
  • [28] Towards real-time DNA biometrics using GPU-accelerated processing
    Reja, Mario
    Pungila, Ciprian
    Negru, Viorel
    LOGIC JOURNAL OF THE IGPL, 2021, 29 (06) : 906 - 924
  • [29] GPU-Accelerated Foreground Segmentation and Labeling for Real-Time Video Surveillance
    Song, Wei
    Tian, Yifei
    Fong, Simon
    Cho, Kyungeun
    Wang, Wei
    Zhang, Weiqiang
    SUSTAINABILITY, 2016, 8 (10)
  • [30] GPU-Accelerated Graph Label Propagation for Real-Time Fraud Detection
    Ye, Chang
    Li, Yuchen
    He, Bingsheng
    Li, Zhao
    Sun, Jianling
    SIGMOD '21: PROCEEDINGS OF THE 2021 INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA, 2021, : 2348 - 2356