Fuzzy segmentation of X-ray fluoroscopy images

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, andsoft tissue that correspondto certain fluoroscopy image values andthen assigning each value to a probability distribution over its most likely generating paths. We then evaluate this segmentation on ground truth patient data. Keywords: fuzzy segmentation, fluoroscopy, probabilistic DRR, image registration, CT. 1