title: Dataset exploited for the development and validation of automated cyanobacteria quantification algorithm, ACQUA.
abstract: The estimation and quantification of potentially toxic cyanobacteria in lakes and reservoirs are often used as a proxy of risk for water intended for human consumption and recreational activities. Here, we present data sets collected from three volcanic Italian lakes (Albano, Vico, Nemi) that present filamentous cyanobacteria strains at different environments. Presented data sets were used to estimate abundance and morphometric characteristics of potentially toxic cyanobacteria comparing manual Vs. automated estimation performed by ACQUA ("ACQUA: Automated Cyanobacterial Quantification Algorithm for toxic filamentous genera using spline curves, pattern recognition and machine learning" (Gandola et al., 2016) [1]). This strategy was used to assess the algorithm performance and to set up the denoising algorithm. Abundance and total length estimations were used for software development, to this aim we evaluated the efficiency of statistical tools and mathematical algorithms, here described. The image convolution with the Sobel filter has been chosen to denoise input images from background signals, then spline curves and least square method were used to parameterize detected filaments and to recombine crossing and interrupted sections aimed at performing precise abundances estimations and morphometric measurements.
authors: University of Rome Tor Vergata, Department of Biology, Via della Ricerca Scientifica 1, 00133 Rome, Italy; Department of Mathematics, University of Rome Tor Vergata, Via della Ricerca Scientifica 1, 00133 Rome, Italy.
authors: Emanuele
authors: E
authors: Gandola
authors: University of Rome Tor Vergata, Department of Biology, Via della Ricerca Scientifica 1, 00133 Rome, Italy; National Institute for Infectious Diseases 'L. Spallanzani' IRCCS, Via Portuense, 292, 00149 Rome, Italy; Freiburg Institute for Advanced Studies (FRIAS), University of Freiburg, Freiburg 79104, Germany.
authors: Manuela
authors: M
authors: Antonioli
authors: The University of Manchester, Jodrell Bank Centre for Astrophysics, School of Physics and Astronomy, Manchester M13 9PL, UK.
authors: Alessio
authors: A
authors: Traficante
authors: University of Rome Tor Vergata, Department of Biology, Via della Ricerca Scientifica 1, 00133 Rome, Italy.
authors: Simone
authors: S
authors: Franceschini
authors: University of Rome Tor Vergata, Department of Biology, Via della Ricerca Scientifica 1, 00133 Rome, Italy.
authors: Michele
authors: M
authors: Scardi
authors: University of Rome Tor Vergata, Department of Biology, Via della Ricerca Scientifica 1, 00133 Rome, Italy; AlgaRes, Spin off of University of Rome Tor Vergata, Via della Ricerca Scientifica 1, 00133 Rome, Italy.
authors: Roberta
authors: R
authors: Congestri
keywords: Algorithm; Comparing data; Deoising; Filamentous cyanobacteria; Natural sample