Graphics processing unit (GPU) implementation of image processing algorithms to improve system performance of the control acquisition, processing, and image display system (CAPIDS) of the micro-angiographic fluoroscope (MAF)

S. N. Swetadri Vasan; Ciprian N. Ionita; A. H. Titus; A. N. Cartwright; D. R. Bednarek; S. Rudin

doi:10.1117/12.911272

23 February 2012 Graphics processing unit (GPU) implementation of image processing algorithms to improve system performance of the control acquisition, processing, and image display system (CAPIDS) of the micro-angiographic fluoroscope (MAF)

S. N. Swetadri Vasan, Ciprian N. Ionita, A. H. Titus, A. N. Cartwright, D. R. Bednarek, S. Rudin

Author Affiliations +

Proceedings Volume 8313, Medical Imaging 2012: Physics of Medical Imaging; 83134C (2012) https://doi.org/10.1117/12.911272
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

Abstract

We present the image processing upgrades implemented on a Graphics Processing Unit (GPU) in the Control, Acquisition, Processing, and Image Display System (CAPIDS) for the custom Micro-Angiographic Fluoroscope (MAF) detector. Most of the image processing currently implemented in the CAPIDS system is pixel independent; that is, the operation on each pixel is the same and the operation on one does not depend upon the result from the operation on the other, allowing the entire image to be processed in parallel. GPU hardware was developed for this kind of massive parallel processing implementation. Thus for an algorithm which has a high amount of parallelism, a GPU implementation is much faster than a CPU implementation. The image processing algorithm upgrades implemented on the CAPIDS system include flat field correction, temporal filtering, image subtraction, roadmap mask generation and display window and leveling. A comparison between the previous and the upgraded version of CAPIDS has been presented, to demonstrate how the improvement is achieved. By performing the image processing on a GPU, significant improvements (with respect to timing or frame rate) have been achieved, including stable operation of the system at 30 fps during a fluoroscopy run, a DSA run, a roadmap procedure and automatic image windowing and leveling during each frame.

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S. N. Swetadri Vasan, Ciprian N. Ionita, A. H. Titus, A. N. Cartwright, D. R. Bednarek, and S. Rudin "Graphics processing unit (GPU) implementation of image processing algorithms to improve system performance of the control acquisition, processing, and image display system (CAPIDS) of the micro-angiographic fluoroscope (MAF)", Proc. SPIE 8313, Medical Imaging 2012: Physics of Medical Imaging, 83134C (23 February 2012); https://doi.org/10.1117/12.911272

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