Bone Fracture Detection Using Morphological and Comparing the Accuracy with Genetic Algorithm
DOI:
https://doi.org/10.47750/pnr.2022.13.S04.030Keywords:
Image Segmentation, X-ray, Morphological algorithm, Bone Fracture Detection, Deep Learning, Genetic Algorithm, Novel Feature Extraction.Abstract
Aim: The purpose of this study is Bone fracture detection using Morphological algorithm and comparing the accuracy with Genetic Algorithm.
Materials And Method: A total of 32 samples wrist fracture dataset from kaggle. Morphological and Genetic algorithms are used to analyze the Bone fracture with a G-power value of 80 %.
Results: From the MATLAB simulation, Morphological achieved 87.46 % accuracy rate compared to 83.25 % accuracy rate by Genetic algorithm. The P value is 0.029 in statistical analysis.
Conclusion: From this case study it is concluded that the image segmentation, Morphological algorithm and Novel feature extraction gives high accuracy compared to the Genetic algorithm based on dataset and morphology developed from Edge detection
