Pit Pattern Classification of Zoom-Endoscopical Colon Images Using DCT and FFT

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http://doi.ieeecomputersociety.org/10.1109/CBMS.2007.85

Twentieth IEEE International Symposiu ...

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	Similar Articles Articles by Michael Hafner Articles by Leonhard Brunauer Articles by Hannes Payer Articles by Robert Resch Articles by Friedrich Wrba Articles by Alfred Gangl Articles by Andreas Vecsei Articles by Andreas Uhl

	ASCII Text	x
	Michael Hafner, Leonhard Brunauer, Hannes Payer, Robert Resch, Friedrich Wrba, Alfred Gangl, Andreas Vecsei, Andreas Uhl, "Pit Pattern Classification of Zoom-Endoscopical Colon Images Using DCT and FFT," Computer-Based Medical Systems, IEEE Symposium on, pp. 159-164, Twentieth IEEE International Symposium on Computer-Based Medical Systems (CBMS'07), 2007.

	BibTex	x
	@article{ 10.1109/CBMS.2007.85, author = {Michael Hafner and Leonhard Brunauer and Hannes Payer and Robert Resch and Friedrich Wrba and Alfred Gangl and Andreas Vecsei and Andreas Uhl}, title = {Pit Pattern Classification of Zoom-Endoscopical Colon Images Using DCT and FFT}, journal ={Computer-Based Medical Systems, IEEE Symposium on}, volume = {0}, year = {2007}, issn = {1063-7125}, pages = {159-164}, doi = {http://doi.ieeecomputersociety.org/10.1109/CBMS.2007.85}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Computer-Based Medical Systems, IEEE Symposium on TI - Pit Pattern Classification of Zoom-Endoscopical Colon Images Using DCT and FFT SN - 1063-7125 SP159 EP164 A1 - Michael Hafner, A1 - Leonhard Brunauer, A1 - Hannes Payer, A1 - Robert Resch, A1 - Friedrich Wrba, A1 - Alfred Gangl, A1 - Andreas Vecsei, A1 - Andreas Uhl, PY - 2007 KW - null VL - 0 JA - Computer-Based Medical Systems, IEEE Symposium on ER -

Michael Hafner, Vienna Medical University

Leonhard Brunauer, Salzburg University

Hannes Payer, Salzburg University

Robert Resch, Salzburg University

Friedrich Wrba, Vienna Medical University

Alfred Gangl, Vienna Medical University

Andreas Vecsei, St. Anna Children's Hospital

Andreas Uhl, Salzburg University

This work presents a classification approach for images taken from magnifying colonoscopy. Classification is done according to the pit pattern scheme. Images are not classified directly in the proposed classifier. Instead, they are transformed to a frequency domain using discrete cosine or Fourier transformation. Feature selection is optimized using a genetic algorithm, the actual classification is done using standard methods from statistical pattern recognition (a Bayes normal classifier).

Citation:

Michael Hafner, Leonhard Brunauer, Hannes Payer, Robert Resch, Friedrich Wrba, Alfred Gangl, Andreas Vecsei, Andreas Uhl, "Pit Pattern Classification of Zoom-Endoscopical Colon Images Using DCT and FFT," cbms, pp.159-164, Twentieth IEEE International Symposium on Computer-Based Medical Systems (CBMS'07), 2007

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