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Freyer, M. ; Ale, A.B.F. ; Schulz, R.B. ; Zientkowska, M. ; Ntziachristos, V. ; Englmeier, K.-H.

Fast automatic segmentation of anatomical structures in x-ray computed images to improve fluorescence molecular tomography reconstruction.

J. Biomed. Opt. 15:036006 (2010)
DOI PMC
Open Access Gold möglich sobald Verlagsversion bei der ZB eingereicht worden ist.
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.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Automatic image segmentation; X-ray computed tomography; Fluorescence molecular tomography; Laplace regularized reconstruction
ISSN (print) / ISBN 1083-3668
e-ISSN 1560-2281
Zeitschrift Journal of Biomedical Optics
Quellenangaben Band: 15, Heft: 3, Seiten: , Artikelnummer: 036006 Supplement: ,
Verlag SPIE
Verlagsort Bellingham, WA
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Biological and Medical Imaging (IBMI)