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An inversion scheme for hybrid fluorescence molecular tomography using a fuzzy inference system.
IEEE Trans. Med. Imaging 35, 381-390 (2016)
The imaging performance of fluorescence molecular tomography (FMT) improves when information from the underlying anatomy is incorporated into the inversion scheme, in the form of priors. The requirement for incorporation of priors has recently driven the development of hybrid FMT systems coupled to other modalities, such as X-ray CT and MRI. A critical methodological aspect in this case relates to the particular method selected to incorporate prior information obtained from the anatomical imaging modality into the FMT inversion. We propose herein a new approach for utilizing prior information, which preferentially minimizes residual errors associated with measurements that better describe the anatomical segments considered. This preferential minimization was realized using a weighted least square (WLS) approach, where the weights were optimized using a Mamdani-type fuzzy inference system. The method of priors introduced herein was deployed as a two-step structured regularization approach and was verified with experimental measurements from phantoms as well as ex vivo and in vivo animal studies. The results demonstrate accurate performance and minimization of reconstruction bias, without requiring user input for setting the regularization parameters. As such, the proposed method offers significant progress in incorporation of anatomical priors in FMT and, as a result, in realization of the full potential of hybrid FMT.
Impact Factor
Scopus SNIP
Web of Science
Times Cited
Times Cited
Scopus
Cited By
Cited By
Altmetric
3.756
2.580
18
20
Anmerkungen
Besondere Publikation
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Publikationstyp
Artikel: Journalartikel
Dokumenttyp
Wissenschaftlicher Artikel
Schlagwörter
Anatomical Priors ; Fluorescence ; Fmt ; Fuzzy Systems ; Hybrid Imaging ; Molecular Imaging ; Optical Imaging ; Tomography; Ray Computed-tomography; X-ray; In-vivo; Imaging-system; Mediated Tomography; Small Animals; Born Ratio; Mri; Regularization; Information
Sprache
englisch
Veröffentlichungsjahr
2016
Prepublished im Jahr
2015
HGF-Berichtsjahr
2015
ISSN (print) / ISBN
0278-0062
e-ISSN
1558-254X
Zeitschrift
IEEE Transactions on Medical Imaging
Quellenangaben
Band: 35,
Heft: 2,
Seiten: 381-390
Verlag
Institute of Electrical and Electronics Engineers (IEEE)
Verlagsort
New York, NY [u.a.]
Begutachtungsstatus
Peer reviewed
POF Topic(s)
30205 - Bioengineering and Digital Health
Forschungsfeld(er)
Enabling and Novel Technologies
PSP-Element(e)
G-505500-001
PubMed ID
26340771
WOS ID
WOS:000370745600002
Erfassungsdatum
2015-09-10