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International MICCAI Workshop on Medical Computer Vision

MCV 2013: Medical Computer Vision. Large Data in Medical Imaging pp 196–204Cite as

Feature Extraction with Intrinsic Distortion Correction in Celiac Disease Imagery: No Need for Rasterization

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8331))

Abstract

In the fields of computer aided celiac disease diagnosis, wide-angle endoscopy lenses are employed which introduce a significant degree of barrel type distortion. In recent studies on celiac disease classification, distortion correction techniques are investigated which use interpolation techniques, in order to maintain the rasterization of the image. Subsequent feature extraction is based on the new images. We introduce a generic feature extraction methodology with intrinsic distortion correction, which does not include this rasterization for features which do not need a regular grid. As distortion correction turned out to be disadvantageous in most cases, we aim in investigating the (negative) effect of the applied rasterization. In our experiments, the omission of rasterization actually turns out to be advantageous. This fact is an incentive for developing more features, which are not based on a regular grid.

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Acknowledgment

This work is partially funded by the Austrian Science Fund (FWF) under (Project No. 24366).

Author information

Authors and Affiliations

  1. Department of Computer Sciences, University of Salzburg, Salzburg, Austria

    Michael Gadermayr & Andreas Uhl

  2. Endoscopy Unit, St. Anna Children’s Hospital, Vienna, Austria

    Andreas Vécsei

Authors
  1. Michael Gadermayr
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  2. Andreas Uhl
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  3. Andreas Vécsei
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Corresponding author

Correspondence to Michael Gadermayr .

Editor information

Editors and Affiliations

  1. Technical University of Munich, ETH, Zürich, Switzerland, Munich, Germany

    Bjoern Menze

  2. Medical University of Vienna, Vienna, Austria

    Georg Langs

  3. GE Global Research, Niskayuna, New York, USA

    Albert Montillo

  4. Siemens AG, Erlangen, Germany

    Michael Kelm

  5. University of Applied Sciences Western Switzerland, Sierre, Switzerland

    Henning Müller

  6. University of California, La Jolla, California, USA

    Zhuowen Tu

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Gadermayr, M., Uhl, A., Vécsei, A. (2014). Feature Extraction with Intrinsic Distortion Correction in Celiac Disease Imagery: No Need for Rasterization. In: Menze, B., Langs, G., Montillo, A., Kelm, M., Müller, H., Tu, Z. (eds) Medical Computer Vision. Large Data in Medical Imaging. MCV 2013. Lecture Notes in Computer Science(), vol 8331. Springer, Cham. https://doi.org/10.1007/978-3-319-05530-5_19

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  • DOI: https://doi.org/10.1007/978-3-319-05530-5_19

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-05529-9

  • Online ISBN: 978-3-319-05530-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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