Predicting the histology of colorectal lesions in a probabilistic framework

@article{Kwitt2010PredictingTH,
  title={Predicting the histology of colorectal lesions in a probabilistic framework},
  author={R. Kwitt and A. Uhl and M. H{\"a}fner and A. Gangl and F. Wrba and A. V{\'e}csei},
  journal={2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops},
  year={2010},
  pages={103-110}
}
  • R. Kwitt, A. Uhl, +3 authors A. Vécsei
  • Published 2010
  • Computer Science
  • 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops
  • In this paper, we present a novel approach to predict the histological diagnosis of colorectal lesions from high-magnification colonoscopy images by means of Pit Pattern analysis. Motivated by the shortcomings of discriminant classifier approaches, we present a generative model based strategy which is closely related to content-based image retrieval (CBIR) systems. The ingredients of the approach are the Dual-Tree Complex Wavelet Transform (DTCWT) and the mathematical construct of copulas. Our… CONTINUE READING

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