Alexandre Fong

Director, Hyperspectral Imaging

Mr. Fong is Director, Hyperspectral Imaging at HinaLea Imaging. He was previously Senior Vice-President , Life Sciences and Instrumentation and Business Development at Gooch & Housego and held technical and commercial leadership positions at ITT Cannon, Newport Corporation, Honeywell and Teledyne Optech. He holds undergraduate and graduate degrees in Experimental Physics from York University in Toronto, Canada, an MBA from the University of Florida and is a Chartered Engineer. Mr. Fong is a published author and lecturer in the fields of precision light measurement, life sciences imaging, remote sensing, applied optics and lasers. He has served on the board of the OSA as well as Chair of the Public Policy Committee, Chair of the OSA Industry Development Associates and Contributing Editor to Optics and Photonics News, he is also an active member of SPIE as a former member of the Financial Advisory Committee and the International Commission on Illumination (CIE). Alex is the current president of the Florida Photonics Cluster.

Spectral angle mapping (SAM) allowed differentiation of cells imaged using hyperspectral dark-field microscopy. Cells below the threshold spectral angle are marked as positive using a green outline; cells above the threshold are marked as negative with a red outline. Isolate cell detection shows positive E. coli 157:H7 (a) and Listeria monocytogenes (b). A slide with both pathogens depict E. coli (c) at positive (48) and negative (65), and Listeria monocytogenes (d) at positive (66) and negative (47).
Detectors & Imaging

Pathogen detection with hyperspectral dark-field microscopy

July 14, 2020
Aided by deep learning, hyperspectral imaging facilitates high-speed single-cell pathogen detection with no critical volume and little prep.
FIGURE 1. The basic principle of a Fabry-Perot interference filter is detailed.
Detectors & Imaging

Hyperspectral Imaging: Hyperspectral microscopy serves biological pathology

Aug. 1, 2018
Spectral unmixing and other image processing techniques applied to hyperspectral data reveal subtle color and texture differences not seen in standard microscopy images, improving...
FIGURE 1. The number of wavelengths used in multispectral analysis impacts spectral unmixing image quality: full-color image (a), primary stain images vs. number of wavelengths (b), relative unmixing quality obtained by quantifying the image contrast vs. number of wavelengths (c), and spectra used for the unmixing (d).

SPECTRAL IMAGING: Real-time spectral unmixing enhances understanding of cellular biomarkers

Nov. 14, 2014
Aided by acousto-optic tunable filters and spectral unmixing, multispectral imaging promises benefits for applications from vital signs monitoring and cancer detection to neuroscience...