Fuzzy segmentation of x-ray fluoroscopy images

Daniel B. Russakoff; Torsten Rohlfing; Calvin R. Maurer Jr.

doi:10.1117/12.467102

9 May 2002 Fuzzy segmentation of x-ray fluoroscopy images

Daniel B. Russakoff, Torsten Rohlfing, Calvin R. Maurer Jr.

Proceedings Volume 4684, Medical Imaging 2002: Image Processing; (2002) https://doi.org/10.1117/12.467102
Event: Medical Imaging 2002, 2002, San Diego, California, United States

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.

Citation Download Citation

Daniel B. Russakoff, Torsten Rohlfing, and Calvin R. Maurer Jr. "Fuzzy segmentation of x-ray fluoroscopy images", Proc. SPIE 4684, Medical Imaging 2002: Image Processing, (9 May 2002); https://doi.org/10.1117/12.467102

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