title: Fast automatic segmentation of anatomical structures in x-ray computed tomography images to improve fluorescence molecular tomography reconstruction.
abstract: The recent development of hybrid imaging scanners that integrate fluorescence molecular tomography (FMT) and x-ray computed tomography (XCT) allows the utilization of x-ray information as image priors for improving optical tomography reconstruction. To fully capitalize on this capacity, we consider a framework for the automatic and fast detection of different anatomic structures in murine XCT images. To accurately differentiate between different structures such as bone, lung, and heart, a combination of image processing steps including thresholding, seed growing, and signal detection are found to offer optimal segmentation performance. The algorithm and its utilization in an inverse FMT scheme that uses priors is demonstrated on mouse images.
authors.affiliation: Technical University Munich, Biological Imaging, Munich, Germany. marcus.freyer@helmholtz-muenchen.de
authors.forename: Marcus
authors.initials: M
authors.lastname: Freyer
authors.forename: Angelique
authors.initials: A
authors.lastname: Ale
authors.forename: Ralf B
authors.initials: RB
authors.lastname: Schulz
authors.forename: Marta
authors.initials: M
authors.lastname: Zientkowska
authors.forename: Vasilis
authors.initials: V
authors.lastname: Ntziachristos
authors.forename: Karl-Hans
authors.initials: KH
authors.lastname: Englmeier
mesh_terms: D000465:Algorithms; D000818:Animals; D006321:Heart / Q000033:anatomy & histology / Q000000981:diagnostic imaging; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008168:Lung / Q000033:anatomy & histology / Q000000981:diagnostic imaging; D051379:Mice; D015233:Models, Statistical; D015203:Reproducibility of Results; D012272:Ribs / Q000033:anatomy & histology / Q000000981:diagnostic imaging; D013050:Spectrometry, Fluorescence / Q000379:methods*; D014057:Tomography, X-Ray Computed / Q000379:methods*