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Computer Assisted Minimal Invasive Surgery towards Guided Motor Control. Vinay B Gavirangaswamy. Canny edge detection algorithm. Output. Original. Single Threaded. Output (contd.). Original . Multi-Threaded ( OpenMP ). Output (contd.). Original. Multi-Threaded (GPU-CUDA).
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Computer Assisted Minimal Invasive Surgery towards Guided Motor Control Vinay B Gavirangaswamy
Output Original Single Threaded
Output (contd.) Original Multi-Threaded (OpenMP)
Output (contd.) Original Multi-Threaded (GPU-CUDA)
Performance Analysis on OpenMP (contd.) Speedup of Canny Algorithm Efficiency of Canny Algorithm
Canny Edge Algorithm Performance on CUDA CS6260 Project Implementation
Canny Edge Detection Performance on CUDA With Different Block Size Runtimes Runtimes serial vs. parallel
Canny Edge Detection Performance on CUDA With Different Block Size (Contd.) Speedup Speedup serial vs. parallel
Canny Edge Detection Performance on CUDA With Different Block Size (Contd.) Efficiency Efficiency serial vs. parallel
Canny Edge Detection Performance on CUDA With Different #Threads Runtimes Runtimes serial vs. parallel
Canny Edge Detection Performance on CUDA With Different #Threads (Contd.) Speedup Speedup serial vs. parallel
Canny Edge Detection Performance on CUDA With Different #Threads (Contd.) Efficiency Efficiency serial vs. parallel
Prediction Based on State Transition Probability • If we want to know probability of the sequence SUNNY SUNNYSUNNYSUNNYSUNNY • Take initial probablity of SUNNY day i.e. on a any given day probability that it will be SUNNY is 0.30 • And for use to get another SUNNY day after a SUNNY day is 0.42 • So, by using Markov Chain we can say prbability of getting 5 consecutive SUNNY day is
Summary • Canny and Markov Chain Model is a simple and efficient way to perform edge detection however canny performs poorly with images taken during laparoscopy (good to get started) • Future work • Contribute improvements to MIS learning methodology.
REFERENCES • Image Convolution with CUDA – Victor Podlozhnyuk, sdkfeedback@nvidia.com • Performance Evaluation of Feature Extraction Algorithm on GPGPU – NamdevSawant Dept. of Computer Science and Engg. Dinesh Kulkarni Dept. of Information Technology, 2011 International Conference on Communication Systems and Network Technologies • Canny Edge Detection on NVIDIA CUDA - Yuancheng “Mike” Luo and RamaniDuraiswami, Perceptual Interfaces and Reality Laboratory, Computer Science & UMIACS, University of Maryland, College Park • Cuda-grayscale – Karlphil, karlphil...@gmail.com • Rich, E.A. 2007. Automata, computability and complexity: Theory and applications, Upper Saddle River, NJ: Prentice Hall • Special thanks to Jason and Vasilije!