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The Colored X-Rays

  • André Aichert
  • Matthias Wieczorek
  • Jian Wang
  • Matthias Kreiser
  • Lejing Wang
  • Pascal Fallavollita
  • Nassir Navab
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7815)

Abstract

Medical imaging has come a long way since the first X-Ray pictures were taken in 1895 and X-Ray is still a primary image source for diagnosis and intra-operative guidance in today’s clinical setting. However, grayscale X-Ray images have some limitations, especially lacking proper depth cues visible to the clinician. In the area of psychology, color has been deemed as self-sufficient depth cues in the visual field. Thus, the focus of this work is integrating color directly in X-Ray in order to disambiguate the sequences of anatomy and hence provide intelligent depth cues for quicker X-Ray interpretation. To achieve this we register pre-operative CT data and X-Ray. A new transfer function is derived using depth and intensity for color emission. Results from a questionnaire to surgeons and medical imaging experts and Likert scale show a positive result of 4.4 average on a 5 scale. Furthermore, we assess the impact of misalignment of the pre-operative CT data and show that the color X-Ray image is very resilient to such errors.

Keywords

Digital Subtraction Angiography Depth Perception Registration Error Ultrasound Plane Percent Correct Match 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • André Aichert
    • 1
  • Matthias Wieczorek
    • 1
  • Jian Wang
    • 1
  • Matthias Kreiser
    • 1
  • Lejing Wang
    • 1
  • Pascal Fallavollita
    • 1
  • Nassir Navab
    • 1
  1. 1.Chair for Computer Aided Medical Procedures (CAMP)Technische Universität MünchenMunichGermany

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