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Analyze and Differentiate Uric Acid Stones and Calcium Stones from Images Using Statistical Parameters


Affiliations
1 Department of Computer Science, Chikkanna Government Arts College, India
2 Department of Information Technology, CMR Institute of Management Studies, India
     

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Image analysis plays a vital role in medical diagnostics. Analysing texture is a major source of discrimination in image analysis. In this paper, we have worked on and analysed images of kidney stones to differentiate between the chemical compositions of different types of stone. The most common types of stones are Calcium and Uric acid stone, hence our study focuses on these two categories. Identifying chemical composition is very crucial as it helps the patients to keep a control on their diet. A statistical comparison is made between these two categories and we have observed significant difference in various classic parameters. A new approach is presented that uses only selected statistical parameters and hence it differs from all previous approaches that differentiates the different types of stones from images without clinical interference.

Keywords

Image Analysis, Uric Acid Stones, Calcium Stones, Entropy, Energy.
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  • Analyze and Differentiate Uric Acid Stones and Calcium Stones from Images Using Statistical Parameters

Abstract Views: 159  |  PDF Views: 0

Authors

G. M. Nasira
Department of Computer Science, Chikkanna Government Arts College, India
M. Ranjitha
Department of Information Technology, CMR Institute of Management Studies, India

Abstract


Image analysis plays a vital role in medical diagnostics. Analysing texture is a major source of discrimination in image analysis. In this paper, we have worked on and analysed images of kidney stones to differentiate between the chemical compositions of different types of stone. The most common types of stones are Calcium and Uric acid stone, hence our study focuses on these two categories. Identifying chemical composition is very crucial as it helps the patients to keep a control on their diet. A statistical comparison is made between these two categories and we have observed significant difference in various classic parameters. A new approach is presented that uses only selected statistical parameters and hence it differs from all previous approaches that differentiates the different types of stones from images without clinical interference.

Keywords


Image Analysis, Uric Acid Stones, Calcium Stones, Entropy, Energy.