You are all cordially invited to the AMLab seminar on Tuesday **May 9** at 16:00 in C3.163, where **Raghavendra Selvan (University of Copenhagen)** will give a talk titled “**Segmenting Tree Structures with Probabilistic State-space Models and Bayesian Smoothing**”. Afterwards there are the usual drinks and snacks!

**Abstract**: Segmenting tree structures is common in several image processing applications. In medical image analysis, reliable segmentations of airways, vessels, neurons and other tree structures can enable important clinical applications. We present a method for extracting tree structures comprising of elongated branches by performing linear Bayesian smoothing in a probabilistic state-space. We apply this method to segment airway trees, wherein, airway states are estimated using the RTS (Rauch-Tung-Striebel) smoother, starting from several automatically detected seed points from across the volume. The RTS smoother tracks airways from seed points, providing Gaussian density approximations of the state estimates. We use covariance of the marginal smoothed density for each airway branch to discriminate true and false positives. Preliminary evaluation shows that the presented method results in additional branches compared to base-line methods.