title: Interactive-cut: Real-time feedback segmentation for translational research.
abstract: In this contribution, a scale-invariant image segmentation algorithm is introduced that "wraps" the algorithm's parameters for the user by its interactive behavior, avoiding the definition of "arbitrary" numbers that the user cannot really understand. Therefore, we designed a specific graph-based segmentation method that only requires a single seed-point inside the target-structure from the user and is thus particularly suitable for immediate processing and interactive, real-time adjustments by the user. In addition, color or gray value information that is needed for the approach can be automatically extracted around the user-defined seed point. Furthermore, the graph is constructed in such a way, so that a polynomial-time mincut computation can provide the segmentation result within a second on an up-to-date computer. The algorithm presented here has been evaluated with fixed seed points on 2D and 3D medical image data, such as brain tumors, cerebral aneurysms and vertebral bodies. Direct comparison of the obtained automatic segmentation results with costlier, manual slice-by-slice segmentations performed by trained physicians, suggest a strong medical relevance of this interactive approach.
authors.affiliation: Department of Mathematics and Computer Science, University of Marburg, Germany; Clinic for Neurosurgery, University Hospital of Marburg, Germany; Institute for Computer Graphics and Vision, Graz University of Technology, Graz, Austria. Electronic address: egger@uni-marburg.de.
authors.forename: Jan
authors.initials: J
authors.lastname: Egger
authors.affiliation: Department of Mechatronics, Technical University of Munich (TUM), Munich, Germany.
authors.forename: Tobias
authors.initials: T
authors.lastname: Lüddemann
authors.affiliation: Department of Mathematics and Computer Science, University of Marburg, Germany.
authors.forename: Robert
authors.initials: R
authors.lastname: Schwarzenberg
authors.affiliation: Department of Mathematics and Computer Science, University of Marburg, Germany.
authors.forename: Bernd
authors.initials: B
authors.lastname: Freisleben
authors.affiliation: Clinic for Neurosurgery, University Hospital of Marburg, Germany.
authors.forename: Christopher
authors.initials: C
authors.lastname: Nimsky
mesh_terms: D000465:Algorithms; D059925:Anatomic Landmarks / Q000473:pathology*; D001921:Brain / Q000473:pathology*; D001927:Brain Diseases / Q000473:pathology*; D003199:Computer Systems; D005246:Feedback; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D057170:Translational Research, Biomedical / Q000379:methods; D014584:User-Computer Interface
keywords: Free drawing templates; Graph-cut; Interactive; Predefined templates; Real-time; Scale-invariant; Segmentation; Template-based; Translational research