T. Sugiura, D. Deguchi, M. Feuerstein, T. Kitasaka, Y. Suenaga, K. Mori A method for accelerating bronchoscope tracking based on image registration by using GPU SPIE Medical Imaging, Orlando, Florida, USA, February 2009 (bib)
	This paper presents a method for accelerating bronchoscope tracking based on image registration by using GPU. Parallel techniques for efficient utilization of a CPU 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. To realize this system, it is indispensable to track the motion of the bronchoscope camera installed 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 (VB) 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 (Graphics Processing Unit) of the graphics card and the CUDA (Compute Unified Device Architecture) language. In particular, we accelerate two parts: (1) VB 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 a rubber bronchial phantom, respectively, and their corresponding CT data sets. The experimental results showed that the proposed method can track a bronchoscope 16 times faster than the previous method only utilizing CPU.
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