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

Conclusion 
 
In this bone fracture detection, a comparative analysis of performance and evaluation of morphological and 
genetic was trained out using RGB coloured images for image segmentation with Novel Feature Extraction. The 
results of these experiments show that morphology has increased better in terms of accuracy than Genetic and is 
less sensitive to the partial blockage. 
Declarations 
 
Conflict of interest 
No conflict of interest in this manuscript.
 
Authors Contributions 
Author YR was involved in data collection, data analysis and manuscript writing. Author AA was involved in 
conceptualization, data validation and critical reviews of manuscript. 
Acknowledgement 
The authors would like to express their gratitude towards Saveetha School of Engineering, Saveetha Institute of 
Medical and Technical Sciences (Formerly Known as Saveetha University) for providing the necessary 
infrastructure to carry out this work successfully. 
Funding
We thank the following organizations for providing financial support that enabled us to complete the study. 

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Journal of Pharmaceutical Negative Results ¦Volume13¦SpecialIssue 4¦2022
273
 
Y. Rakesh
,
etal
.:
Bone Fracture Detection Using Morphological and Comparing the Accuracy with Genetic Algorithm 
1. VK Technologies, Chennai. 
2. Saveetha University 
3. Saveetha Institute of Medical and Technical Sciences 
4. Saveetha School of Engineering 
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Journal of Pharmaceutical Negative Results ¦Volume13¦SpecialIssue 4¦2022