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Mandal, S. ; Dean-Ben, X.L. ; Razansky, D.

Visual quality enhancement in optoacoustic tomography using active contour segmentation priors.

IEEE Trans. Med. Imaging 35, 2209-2217 (2016)
Postprint DOI PMC
Open Access Green
Segmentation of biomedical images is essential for studying and characterizing anatomical structures as well as for detection and evaluation of tissue pathologies. Segmentation has been further shown to enhance the reconstruction performance in many tomographic imaging modalities by accounting for heterogeneities in the excitation field and tissue properties in the imaged region. This is particularly relevant in optoacoustic tomography, where discontinuities in the optical and acoustic tissue properties, if not properly accounted for, may result in deterioration of the imaging performance. Efficient segmentation of optoacoustic images is often hampered by the relatively low intrinsic contrast of large anatomical structures, which is further impaired by the limited angular coverage of some commonly employed tomographic imaging configurations. Herein, we analyze the performance of active contour models for boundary segmentation in cross-sectional optoacoustic tomography. The segmented mask is employed to construct a two compartment model for the acoustic and optical parameters of the imaged tissues, which is subsequently used to improve accuracy of the image reconstruction routines. The performance of the suggested segmentation and modeling approach are showcased in tissuemimicking phantoms and small animal imaging experiments.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Biophotonics ; Image Quality ; Image Segmentation ; Multispectral Imaging ; Photoacoustic Imaging; Photoacoustic Tomography; Scattering Media; Reconstruction; Light; Algorithm; Boundary; Tissues; Snakes; Sound; Flow
Sprache
Veröffentlichungsjahr 2016
HGF-Berichtsjahr 2016
ISSN (print) / ISBN 0278-0062
e-ISSN 1558-254X
Zeitschrift IEEE Transactions on Medical Imaging
Quellenangaben Band: 35, Heft: 10, Seiten: 2209-2217 Artikelnummer: , Supplement: ,
Verlag Institute of Electrical and Electronics Engineers (IEEE)
Verlagsort New York, NY [u.a.]
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Biological and Medical Imaging (IBMI)
POF Topic(s) 30205 - Bioengineering and Digital Health
Forschungsfeld(er) Enabling and Novel Technologies
PSP-Element(e) G-505590-001
DOI 10.1109/TMI.2016.2553156
WOS ID WOS:000385985200001
Scopus ID 84993908991
PubMed ID 27093547
Erfassungsdatum 2016-05-04
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