Supporting data for "Depth-resolved imaging of live plankton with electronically tunable lenses"

This repository contains raw data (images, code, csv-files) supporting the publication "Depth-resolved imaging of live plankton with electronically tunable lenses" wellscanner.tar The main software package for acquiring and analyzing ETL-based image data. It includes a comprehensive (offline) image analysis module for reconstructing swimming paths in 3D and size measurements based on previously recorded image sequences (with the acquisition module). It also includes a realtime module, which continuously acquires sharp image crops of individuals during a livestream of a population. Note that using the image acquisition and realtime module requires that you have the hardware and suitable drivers installed, most notably, for camera and the ETL-objective. raw_data_example.tar Example of a raw image series containing 375frames (25fps recorded for a duration of 15sec) recorded with ETL-optics. This type of data is used by the offline image analysis module to reconstruct swimming paths in 3D and for size measurements. posture_crops_good_bad.tar Training images for the machine learning filter in the offline image analysis (stage 4), to filter out those images in which individuals were captured in an optimal position for size measurement. scan_pattern_test.tar Dataset consisting of photos, diagrams and csv-files, containing the raw data analysis of the Z-scanning patterns "zigzag" and "sawtooth" across seven ETL-step sizes (100–700 µm). The analysis contains the complete output of the offline analysis module on all 70 movies (2 scanning patterns, 7 step sizes, 5 populations/biological replicates), including cropped images of particles, particle csv-lists, figures of the intermediate analysis steps. size_BP_complex.tar Dataset containing the raw images (Lugol-fixed samples vs. live samples) used in the size measurements of multiple species of the B. plicatilis species complex. size_BPcomplex_single.tar Dataset containing the raw images (Lugol-fixed samples vs. live samples) used in the size measurements of multiple species of the B. plicatilis species complex. Here only a single non egg-bearing animal was first photographed live, then fixed in Lugol's solution and then measured again (4 individuals per species). realtime_crops_S5VPJ6415.tar A collection of 175 cropped images, recorded from 15 B. asplanchnoidis rotifers with the realtime mode and the S5VPJ6415 objective (1.5x magnification) during a ~2min time interval. egg_detector.tar Software for the binary classifier of egg-bearing vs. non-egg-bearing rotifers. The 'output' directory contains the trained model and the results of our analysis. The 'data' directory is empty here; if you want rerun our analysis, copy 'egg_detector_data' into this directory. egg_detector_data.tar Dataset containing 7283 images that were used for the binary classifier for egg-bearing vs. non-egg-bearing rotifers (4320 training, 1760 validation, and 1203 test images). Images were generated with the TS1-0638-70-EL objective (0.638-fold magnification).