title: 2D image registration in CT images using radial image descriptors.
abstract: Registering CT scans in a body atlas is an important technique for aligning and comparing different CT scans. It is also required for navigating automatically to certain regions of a scan or if sub volumes should be identified automatically. Common solutions to this problem employ landmark detectors and interpolation techniques. However, these solutions are often not applicable if the query scan is very small or consists only of a single slice. Therefore, the research community proposed methods being independent from landmark detectors which are using imaging techniques to register the slices in a generalized height scale. In this paper, we propose an improved prediction method for registering single slices. Our solution is based on specialized image descriptors and instance-based learning. The experimental evaluation shows that the new method improves accuracy and stability of comparable registration methods by using only a single CT slice is required for the registration.
authors: Institut für Informatik, Ludwig-Maximilians-Universität München Oettingenstr. 67, D-80538 München, Germany. graf@dbs.ifi.lmu.de
authors: Franz
authors: F
authors: Graf
authors: Hans-Peter
authors: HP
authors: Kriegel
authors: Matthias
authors: M
authors: Schubert
authors: Sebastian
authors: S
authors: Pölsterl
authors: Alexander
authors: A
authors: Cavallaro
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D002648:Child; D002675:Child, Preschool; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009333:Neck / Q000473:pathology; D013902:Radiography, Thoracic / Q000379:methods; D012984:Software; D014057:Tomography, X-Ray Computed / Q000379:methods*