Stable 3D Airways Registration from Segmented 3D CT Images

Image registration is an efficient computational technique for diagnosis and diseases monitoring. Lungs airways diseases, such as chronic obstructive pulmonary disease (COPD) and asthma, require periodical checkups and past data comparison to estimate the patient condition. In this work, it is proposed an airways registration algorithm that is performed branch by branch. The branch registration combines the positive aspects from the conventional ICP and skeleton registration algorithms. The registration procedure requires two main modules: point correspondence determination, and transformation determination. The point correspondence determination is the most time consuming and it is performed in high speed using a 3D discrete Voronoi diagram. Copyright c ©2015 IFAC.