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Classification of Human Organ Using Image Processing


Affiliations
1 Department of Computer Sciences, Christ University, Bengaluru, India
 

The collection of large database of digital image has been used for efficient and advanced way for classifying and intelligent retrieval of medical imaging. This research work is to classify human organs based on MRI images. The various MRI images of organ have been considered as the data set. The main objective of this research work is to automate the medical imaging system. Digital images retrieved based on its shape by Canny Edge Detection and is clustered together in one class using K-Means Algorithm. 2564 data sets related to brain and heart is considered for this research work. The system was trained to classify the image which results in faster execution in medical field, also helped in obtain noiseless and efficient data.

Keywords

Medical Imaging, Digital Images, Organs, Canny Edge Detection, K-Means Algorithm.
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  • Classification of Human Organ Using Image Processing

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Authors

Sindhu
Department of Computer Sciences, Christ University, Bengaluru, India
V. Vaidhehi
Department of Computer Sciences, Christ University, Bengaluru, India

Abstract


The collection of large database of digital image has been used for efficient and advanced way for classifying and intelligent retrieval of medical imaging. This research work is to classify human organs based on MRI images. The various MRI images of organ have been considered as the data set. The main objective of this research work is to automate the medical imaging system. Digital images retrieved based on its shape by Canny Edge Detection and is clustered together in one class using K-Means Algorithm. 2564 data sets related to brain and heart is considered for this research work. The system was trained to classify the image which results in faster execution in medical field, also helped in obtain noiseless and efficient data.

Keywords


Medical Imaging, Digital Images, Organs, Canny Edge Detection, K-Means Algorithm.

References





DOI: https://doi.org/10.13005/ojcst%2F10.02.11