Marching cubes: A high resolution 3D surface construction algorithm
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
On calculation of fractal dimension of images
Pattern Recognition Letters
On the Calculation of Fractal Features from Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Intel threading building blocks
Intel threading building blocks
Programming Massively Parallel Processors: A Hands-on Approach
Programming Massively Parallel Processors: A Hands-on Approach
Fast in-place, comparison-based sorting with CUDA: a study with bitonic sort
Concurrency and Computation: Practice & Experience
IEEE Micro
UJA-3DFD: A program to compute the 3D fractal dimension from MRI data
Computer Methods and Programs in Biomedicine
fMRI analysis on the GPU-Possibilities and challenges
Computer Methods and Programs in Biomedicine
Design and implementation of an efficient integer count sort in CUDA GPUs
Concurrency and Computation: Practice & Experience
Box-counting algorithm on GPU and multi-core CPU: an OpenCL cross-platform study
The Journal of Supercomputing
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The box-counting algorithm is one of the most widely used methods for calculating the fractal dimension (FD). The FD has many image analysis applications in the biomedical field, where it has been used extensively to characterize a wide range of medical signals. However, computing the FD for large images, especially in 3D, is a time consuming process. In this paper we present a fast parallel version of the box-counting algorithm, which has been coded in CUDA for execution on the Graphic Processing Unit (GPU). The optimized GPU implementation achieved an average speedup of 28 times (28x) compared to a mono-threaded CPU implementation, and an average speedup of 7 times (7x) compared to a multi-threaded CPU implementation. The performance of our improved box-counting algorithm has been tested with 3D models with different complexity, features and sizes. The validity and accuracy of the algorithm has been confirmed using models with well-known FD values. As a case study, a 3D FD analysis of several brain tissues has been performed using our GPU box-counting algorithm.