Paper
13 March 2009 A method for accelerating bronchoscope tracking based on image registration by using GPU
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Abstract
This paper presents a method for accelerating bronchoscope tracking based on image registration by using the GPU (Graphics Processing Unit). Parallel techniques for efficient utilization of CPU (Central Processing Unit) and GPU in image registration are presented. Recently, a bronchoscope navigation system has been developed for enabling a bronchoscopist to perform safe and efficient examination. In such system, it is indispensable to track the motion of the bronchoscope camera at the tip of the bronchoscope in real time. We have previously developed a method for tracking a bronchoscope by computing image similarities between real and virtual bronchoscopic images. However, since image registration is quite time consuming, it is difficult to track the bronchoscope in real time. This paper presents a method for accelerating the process of image registration by utilizing the GPU of the graphics card and the CUDA (Compute Unified Device Architecture) architexture. In particular, we accelerate two parts: (1) virtual bronchoscopic image generation by volume rendering and (2) image similarity calculation between a real bronchoscopic image and virtual bronchoscopic images. Furthermore, to efficiently use the GPU, we minimize (i) the amount of data transfer between CPU and GPU, and (ii) the number of GPU function calls from the CPU. We applied the proposed method to bronchoscopic videos of 10 patients and their corresponding CT data sets. The experimental results showed that the proposed method can track a bronchoscope at 15 frames per second and 5.17 times faster than the same method only using the CPU.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Takamasa Sugiura, Daisuke Deguchi, Marco Feuerstein, Takayuki Kitasaka, Yasuhito Suenaga, and Kensaku Mori "A method for accelerating bronchoscope tracking based on image registration by using GPU", Proc. SPIE 7261, Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling, 726108 (13 March 2009); https://doi.org/10.1117/12.813491
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
Image processing

Image registration

Volume rendering

Cameras

GPU based image processing

Video

Video acceleration

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