Medical Image Segmentation Using Phase-Field Method based on GPU Parallel Programming

Santoso, Albertus Joko and Pranowo, . (2022) Medical Image Segmentation Using Phase-Field Method based on GPU Parallel Programming. International Association Engineerd IAENG, 30 (1). ISSN 1816-093X

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Abstract

The use of a Phase Field method for medical image segmentation is proposed in this paper. The Allen-Cahn equation, a mathematical model equation, is used in this method. The Finite Difference method is used for numerical discretization of model equations and semi-algebraic equations integrated over time using the second -order Runge-Kutta method. Numerical algorithms are implemented into computer programming using the serial and parallel C programming language based on GPU CUDA. Based on image segmentation calculations, the Phase Field method has high accuracy. It is indicated by the Jaccard Index and Dice Similarity values that are close to one. The range of Jaccard Index values is 0.859 - 0.952, while the Dice Similarity value range is 0.926 - 0.976. In addition, it is shown that parallel programming with GPU CUDA can accelerate 45.72 times compared to serial programming.

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