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Color Image Segmentation Applied to Medical Domain

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Intelligent Data Engineering and Automated Learning - IDEAL 2007 (IDEAL 2007)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4881))

Abstract

The article presents two practical ways of using the automated color image segmentation in the medical field: for content-based region query and for tracking the time evolution of the disease in patients following a certain treatment. A known technique was used for automated color medical image segmentation – the color set back-projection algorithm. Our previous work in extraction of color regions from a database of nature images using the same algorithm showed promising results. The images are transformed from RGB to HSV color space, quantized at 166 colors and processed by the color set back-projection algorithm that allows the color region detection. The algorithm is studied from two points of view: complexity and the retrieval quality. The experiments that were made on a database with color endoscopy images from digestive tract have shown satisfying results for both applications that are important in practical medical use and medical teaching.

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References

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Hujun Yin Peter Tino Emilio Corchado Will Byrne Xin Yao

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© 2007 Springer-Verlag Berlin Heidelberg

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Stanescu, L., Burdescu, D.D., Stoica, C. (2007). Color Image Segmentation Applied to Medical Domain. In: Yin, H., Tino, P., Corchado, E., Byrne, W., Yao, X. (eds) Intelligent Data Engineering and Automated Learning - IDEAL 2007. IDEAL 2007. Lecture Notes in Computer Science, vol 4881. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77226-2_47

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  • DOI: https://doi.org/10.1007/978-3-540-77226-2_47

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77225-5

  • Online ISBN: 978-3-540-77226-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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