TY - JOUR AU - Deglint, jason L. AU - Tang, Lydon AU - Wang, Yitian AU - Jin, Chao AU - Wong, Alexander PY - 2018/12/24 Y2 - 2024/03/29 TI - SAMSON: Spectral Absorption-fluorescence Microscopy System for ON-site-imaging of algae JF - Journal of Computational Vision and Imaging Systems JA - J. Comp. Vis. Imag. Sys. VL - 4 IS - 1 SE - Articles DO - 10.15353/jcvis.v4i1.324 UR - https://openjournals.uwaterloo.ca/index.php/vsl/article/view/324 SP - 3 AB - <p>This paper presents SAMSON, a Spectral Absorption-fluorescence<br>Microscopy System for ON-site-imaging of algae within a water<br>sample. Designed to be portable and low-cost for on-site use,<br>the optical sub-system of SAMSON consists of a mixture of low-<br>cost optics and electronics, designed specifically to capture both<br>fluorescent and absorption responses from a water sample. The<br>graphical user interface (GUI) sub-system of SAMSON was de-<br>signed to enable flexible visualisation of algae in the water sample<br>in real-time, with the ability to perform fine-grained exposure con-<br>trol and illumination wavelength selection. We demonstrate SAM-<br>SON’s capabilities by equipping the system with two fluorescent<br>illumination sources and seven absorption illumination sources to<br>enable the capture of multispectral data from six different algae<br>species (three from the Cyanophyta phylum (blue-green algae) and<br>three from the Chlorophyta phylum (green algae)). The key benefit<br>of SAMSON is the ability to perform rapid acquisition of fluores-<br>cence and absorption data at different wavelengths and magnifica-<br>tion levels, thus opening the door for machine learning methods to<br>automatically identify and enumerate different algae in water sam-<br>ples using this rich wealth of data.</p> ER -