Multi-parametric standardization of fluorescence imaging systems based on a composite phantom.
IEEE Trans. Bio. Med. Eng. 67, 185-192 (2020)
Objective: Fluorescence molecular imaging (FMI) has emerged as a promising tool for surgical guidance in oncology, with one of the few remaining challenges being the ability to offer quality control and data referencing. This paper investigates the use of a novel composite phantom to correct and benchmark FMI systems. Methods: This paper extends on previous work by describing a phantom design that can provide a more complete assessment of FMI systems through quantification of dynamic range and determination of spatial illumination patterns for both reflectance and fluorescence imaging. Various performance metrics are combined into a robust and descriptive "system benchmarking score," enabling not only the comprehensive comparison of different systems, but also for the first time, correction of the acquired data. Results: We show that systems developed for targeted fluorescence imaging can achieve benchmarking scores of up to 70 & x0025;, while clinically available systems optimized for indocyanine green are limited to 50 & x0025;, mostly due to greater leakage of ambient and excitation illumination and lower resolution. The image uniformity can also be approximated and employed for image flat-fielding, an important milestone toward data referencing. In addition, we demonstrate composite phantom use in assessing the performance of a surgical microscope and of a raster-scan imaging system. Conclusion: Our results suggest that the new phantom has the potential to support high-fidelity FMI through benchmarking and image correction. Significance: Standardization of the FMI is a necessary process for establishing good imaging practices in clinical environments and for enabling high-fidelity imaging across patients and multi-center imaging studies.
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Publication type
Article: Journal article
Document type
Scientific Article
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Keywords
Fluorescence Molecular Imaging ; Composite Phantom ; Standardization ; Benchmarking ; Data Referencing
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Publication Year
2020
Prepublished in Year
2019
HGF-reported in Year
2019
ISSN (print) / ISBN
0018-9294
e-ISSN
0096-0616
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Volume: 67,
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Pages: 185-192
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Institute of Electrical and Electronics Engineers (IEEE)
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New York, NY
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Peer reviewed
POF-Topic(s)
30205 - Bioengineering and Digital Health
Research field(s)
Enabling and Novel Technologies
PSP Element(s)
G-505500-001
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Erfassungsdatum
2020-01-09