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Open Access Gold as soon as Publ. Version/Full Text is submitted to ZB.
Fast automatic segmentation of anatomical structures in x-ray computed images to improve fluorescence molecular tomography reconstruction.
J. Biomed. Opt. 15:036006 (2010)
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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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
Automatic image segmentation; X-ray computed tomography; Fluorescence molecular tomography; Laplace regularized reconstruction
ISSN (print) / ISBN
1083-3668
e-ISSN
1560-2281
Journal
Journal of Biomedical Optics
Quellenangaben
Volume: 15,
Issue: 3,
Article Number: 036006
Publisher
SPIE
Publishing Place
Bellingham, WA
Reviewing status
Peer reviewed
Institute(s)
Institute of Biological and Medical Imaging (IBMI)