Bone Fracture Detection Using Morphological and Comparing the Accuracy with Genetic Algorithm Y. Rakesh

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Journal of Pharmaceutical Negative Results ¦Volume13¦SpecialIssue 4¦2022
270
 
Abstract
 
Bone Fracture Detection Using Morphological and 
Comparing the Accuracy with Genetic Algorithm 
Y. Rakesh
1
, A. Akilandeswari
2 
 
1
Research Scholar,Department of Electronics and Communication Engineering,Saveetha School of Engineering,Saveetha 
Institute of Medical and Technical Sciences,Saveetha University, Chennai, Tamilnadu,India,Pincode : 602105. 
2
Project Guide, Corresponding Author,Department of Electronics and Communication Engineering,Saveetha School of 
Engineering,Saveetha Institute of Medical and Technical Sciences,Saveetha University, Chennai, Tamilnadu,India,Pincode : 
602105. 
 
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. 
Keywords: 
Image Segmentation, X-ray, Morphological algorithm, Bone Fracture Detection, Deep Learning, Genetic 
Algorithm, Novel Feature Extraction.