title: [Image post-processing, part 1: visualization and segmentation].
abstract: Image post-processing of large thin-slice radiological datasets relies on increasingly diverse and complex algorithms. Basic techniques of visualization, segmentation and data analysis will be presented in this article focusing on methods which are integrated into the majority of current viewing and reporting tools, such as multiplanar reformation, volume rendering or basic segmentation. Subsequently, more complex methods and a possible role of post-processing algorithms in the radiology of the future will be discussed.
authors.affiliation: Abteilung Röntgendiagnostik, Universitätsklinikum Freiburg, Hugstetter Str. 55, 79106, Freiburg, Deutschland, tobias.baumann@uniklinik-freiburg.de.
authors.forename: T
authors.initials: T
authors.lastname: Baumann
authors.forename: M
authors.initials: M
authors.lastname: Langer
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D014057:Tomography, X-Ray Computed / Q000379:methods*; D014584:User-Computer Interface