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Proceedings Paper

Fuzzy segmentation of x-ray fluoroscopy images
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Paper Abstract

Segmentation of fluoroscopy images is useful for fluoroscopy-to-CT image registration. However, it is impossible to assign a unique tissue type to each pixel. Rather each pixel corresponds to an entire path of tissue types encountered along a ray from the X-ray source to the detector plate. Furthermore, there is an inherent many-to-one mapping between paths and pixel values. We address these issues by assigning to each pixel not a scalar value but a fuzzy vector of tissue probabilities. We perform this segmentation in a probabilistic way by first learning typical distributions of bone, air, and soft tissue that correspond to certain fluoroscopy image values and then assigning each value to a probability distribution over its most likely generating paths. We then evaluate this segmentation on ground truth patient data.

Paper Details

Date Published: 9 May 2002
PDF: 9 pages
Proc. SPIE 4684, Medical Imaging 2002: Image Processing, (9 May 2002); doi: 10.1117/12.467102
Show Author Affiliations
Daniel B. Russakoff, Stanford Univ. (United States)
Torsten Rohlfing, Stanford Univ. (United States)
Calvin R. Maurer Jr., Stanford Univ. (United States)

Published in SPIE Proceedings Vol. 4684:
Medical Imaging 2002: Image Processing
Milan Sonka; J. Michael Fitzpatrick, Editor(s)

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