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Wound Segmentation using Image Segmentation and Artificial Neural Network


Affiliations
1 Department of Information Science & Engineering, JSS Academy of Technical Education, Bangalore, Karnataka, India
2 Department of Information Science & Engineering, JSS Academy of Technical Education, Bangalore, Karnataka, India
     

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Chronic wounds are worldwide, present health challenge burdens a huge number of individuals. The effectual diagnoses and treatment of the wound mainly depend on clear-cut wound identification and wounded tissue measurement. but right now wound evaluation and the clinical process is completely done manually which is not accurate. From the standpoint of improving the final result in wound management and care, which delivers inefficient and economically viable medical treatment/practice, an automated computerized system for speedy and precise wound segmentation and wound identification is needed. The author created a system that leverages patient-provided wound images and performs automated picture segmentation and wound identification. Multilayer perceptron and Radial basis function are the two strategies employed.

Keywords

Artificial Neural Networks, Image Processing, Image Segmentation, Traditional Method.
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  • Wound Segmentation using Image Segmentation and Artificial Neural Network

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Authors

S. Nagashree
Department of Information Science & Engineering, JSS Academy of Technical Education, Bangalore, Karnataka, India
M. Ayesha
Department of Information Science & Engineering, JSS Academy of Technical Education, Bangalore, Karnataka, India
D. Abhishek Kumar
Department of Information Science & Engineering, JSS Academy of Technical Education, Bangalore, Karnataka, India
D. Mohd Sameer
Department of Information Science & Engineering, JSS Academy of Technical Education, Bangalore, Karnataka, India
Syed Nasir Abbas
Department of Information Science & Engineering, JSS Academy of Technical Education, Bangalore, Karnataka, India

Abstract


Chronic wounds are worldwide, present health challenge burdens a huge number of individuals. The effectual diagnoses and treatment of the wound mainly depend on clear-cut wound identification and wounded tissue measurement. but right now wound evaluation and the clinical process is completely done manually which is not accurate. From the standpoint of improving the final result in wound management and care, which delivers inefficient and economically viable medical treatment/practice, an automated computerized system for speedy and precise wound segmentation and wound identification is needed. The author created a system that leverages patient-provided wound images and performs automated picture segmentation and wound identification. Multilayer perceptron and Radial basis function are the two strategies employed.

Keywords


Artificial Neural Networks, Image Processing, Image Segmentation, Traditional Method.

References