Juerg Tschirren

TL;DR: A new airway segmentation method based on fuzzy connectivity that works on various types of scans (low-dose and regular dose, normal subjects and diseased subjects) without the need for the user to manually adjust any parameters is presented.

TL;DR: Curvilinear airway centerline and diameter models have been fitted to human and ovine bronchial trees using detailed data segmented from multidetector row X-ray-computed tomography scans, and the resulting models are subject-specific computational meshes with anatomically consistent geometry suitable for application in simulation studies.

TL;DR: A fusion scheme that obtained superior results is presented, demonstrating that there is complementary information provided by the different algorithms and there is still room for further improvements in airway segmentation algorithms.

TL;DR: With the improved resolution and speed of CT imaging, the patchy nature of regional parenchymal pathology can be imaged as texture of structure and function.

TL;DR: Algorithms that perform both matching of branchpoints and anatomical labeling of in vivo trees without any human intervention and within a short computing time are presented.