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1.
Opt Express ; 25(11): 12812-12829, 2017 May 29.
Article in English | MEDLINE | ID: mdl-28786634

ABSTRACT

Fluorescence imaging can reveal functional, anatomical or pathological features of high interest in medical interventions. We present a novel method to record and display in video rate multispectral color and fluorescence images over the visible and near infrared range. The fast acquisition in multiple channels is achieved through a combination of spectral and temporal multiplexing in a system with two standard color sensors. Accurate color reproduction and high fluorescence unmixing performance are experimentally demonstrated with a prototype system in a challenging imaging scenario. Through spectral simulation and optimization we show that the system is sensitive to all dyes emitting in the visible and near infrared region without changing filters and that the SNR of multiple unmixed components can be kept high if parameters are chosen well. We propose a sensitive per-pixel metric of unmixing quality in a single image based on noise propagation and present a method to visualize the high-dimensional data in a 2D graph, where up to three fluorescent components can be distinguished and segmented.

2.
Opt Lett ; 41(6): 1173-6, 2016 Mar 15.
Article in English | MEDLINE | ID: mdl-26977662

ABSTRACT

Fluorescence-guided surgical procedures are employed in an increasing number of applications such as tumor delineation, blood perfusion, and sentinel lymph node detection. A new generation of fluorescent probes is expected to increase the number of applications and improve efficiency. Yet, there are no available imaging methods to take full advantage of the forthcoming targeting technologies. We present a novel concept for imaging multiple agents for fluorescence-guided surgery. The system operates without any moving parts and can resolve images of three different fluorochromes while simultaneously recording conventional reflectance images.


Subject(s)
Optical Imaging/methods , Surgery, Computer-Assisted/methods , Algorithms , Animals , Cattle , Linear Models , Time Factors
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