Speeding up Mutual Information Computation Using NVIDIA CUDA Hardware

We present an efficient method for mutual information (MI) computation between images (2D or 3D) for NVIDIA's `compute unified device architecture' (CUDA) compatible devices. Efficient parallelization of MI is particularly challenging on a `graphics processor unit' (GPU) due to the need for histogram-based calculation of joint and marginal probability mass functions (pmfs) with large number of bins. The data-dependent (unpredictable) nature of the updates to the histogram, together with hardware limitations of the GPU (lack of synchronization primitives and limited memory caching mechanisms) can make GPU-based computation inefficient. To overcome these limitation, we approximate the pmfs, using a down-sampled version of the joint- histogram which avoids memory update problems. Our CUDA implementation improves the efficiency of MI calculations by a factor of 25 compared to a standard CPU- based implementation and can be used in MI-based image registration applications.

[1]  Anand Rangarajan,et al.  New Method of Probability Density Estimation with Application to Mutual Information Based Image Registration , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[2]  Rodney A. Kennedy,et al.  Gradient Intensity: A New Mutual Information-Based Registration Method , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[3]  Rodney A. Kennedy,et al.  Gradient Intensity-Based Registration of Multi-Modal Images of the Brain , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[4]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[5]  Nassir Navab,et al.  A Novel Projection Based Approach for Medical Image Registration , 2006, WBIR.

[6]  Michael Unser,et al.  Stochastic Sampling for Computing the Mutual Information of Two Images , 2003 .

[7]  Rodney A. Kennedy,et al.  Efficient Histogram Algorithms for NVIDIA CUDA Compatible Devices , 2007 .

[8]  Max A. Viergever,et al.  Mutual-information-based registration of medical images: a survey , 2003, IEEE Transactions on Medical Imaging.

[9]  Nick Barnes,et al.  Image Registration in Hough Space Using Gradient of Images , 2007, 9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications (DICTA 2007).