Results of pseudo-coloring algorithms for a normal thermogram of an individual: original gray-level image, and its pseudo-colorized images in the HSI color space under various conditions.

Results of pseudo-coloring algorithms for a normal thermogram of an individual: original gray-level image, and its pseudo-colorized images in the HSI color space under various conditions.

<p>Results of pseudo-coloring algorithms for a normal thermogram of an individual: original gray-level image, and its pseudo-colorized images in the HSI color space under various conditions.</p>

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Bibliographic Details
Main Author:	Hamed Khodadadi (21446172) (author)
Other Authors:	Shima Nazem (21446175) (author)
Published:	2025
Subjects:	Biotechnology Cancer Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified significant health issue optimize feature selection measures temperature variations including lyapunov exponent improving patient outcomes fitting neural network analyzing breast thermograms 65 %, emphasizes svm ), k pat net ), fit net ), improving cancer detection extracts relevant features kse ), cd ), early detection texture features complexity features superior performance study proposes sinai entropy reduce redundancy proposed method proposed approach promising approach occurrence matrix nsga iii novel method nearest neighbors method utilized level co integrating texture high rates fold cross early diagnosis correlation dimension comprehensive analysis chaotic indices cancerous tissues aided diagnosis achieved accuracy
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Summary:	<p>Results of pseudo-coloring algorithms for a normal thermogram of an individual: original gray-level image, and its pseudo-colorized images in the HSI color space under various conditions.</p>

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