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Related Experiment Video

Updated: Aug 15, 2025

Simultaneous Interference Reflection and Total Internal Reflection Fluorescence Microscopy for Imaging Dynamic Microtubules and Associated Proteins

Simultaneous Interference Reflection and Total Internal Reflection Fluorescence Microscopy for Imaging Dynamic Microtubules and Associated Proteins

Published on: May 3, 2022

CIVIT dataset: Integral microscopy with Fourier plane recording.

Sergio Moreschini¹, Filipe Gama¹, Robert Bregovic¹

¹Tampere University, Korkeakoulunkatu 1, 33720 Tampere, Finland.

|January 2, 2023

Summary

This summary is machine-generated.

This study introduces a synthetic dataset of biological images captured by a Fourier Lightfield Microscope (FLMic). The dataset aids in developing volumetric reconstruction methods for light field microscopy.

Keywords:

Blender Cells DCR, Dynamic Cutting Region DSFL, Densely Sampled Light Field EI, Elemental Image FLMic, Fourier Lightfield Microscope FiMic, Fourier Integral Microscope Filaments Fourier lightfield microscopy GT, Ground Truth LF, Light Field Light field NA, Numerical Apperture RBC, Red Blood Cell RoI, Region of Interest Z-scan Z-stack

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Published on: December 1, 2016

Implementation of Interference Reflection Microscopy for Label-free, High-speed Imaging of Microtubules

Implementation of Interference Reflection Microscopy for Label-free, High-speed Imaging of Microtubules

Published on: August 8, 2019

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Last Updated: Aug 15, 2025

Simultaneous Interference Reflection and Total Internal Reflection Fluorescence Microscopy for Imaging Dynamic Microtubules and Associated Proteins

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Published on: May 3, 2022

Three-dimensional Super Resolution Microscopy of F-actin Filaments by Interferometric PhotoActivated Localization Microscopy iPALM

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Published on: December 1, 2016

Implementation of Interference Reflection Microscopy for Label-free, High-speed Imaging of Microtubules

Implementation of Interference Reflection Microscopy for Label-free, High-speed Imaging of Microtubules

Published on: August 8, 2019

Area of Science:

Microscopy and Imaging
Computational Biology
Computer Vision

Background:

Fourier Lightfield Microscopy (FLMic) offers advanced 3D imaging capabilities.
Development of robust volumetric reconstruction algorithms is crucial for analyzing FLMic data.
Synthetic datasets are valuable for algorithm development and validation in microscopy.

Purpose of the Study:

To present a comprehensive synthetic dataset for Fourier Lightfield Microscope (FLMic) imaging.
To facilitate the development and assessment of volumetric reconstruction techniques for FLMic data.
To provide researchers with standardized data for benchmarking light field microscopy algorithms.

Main Methods:

Generation of 22,416 synthetic images using Blender, simulating biological samples (cells, bacteria).
Creation of eight distinct scenes with 3D models, including 'Cells' and 'Filaments' categories.
Provision of two data structures: 51x51 Elemental Images (EIs) for Densely Sampled Light Fields (DSLF) and Z-Scans.

Main Results:

A diverse dataset comprising 22,416 synthetic images and associated metadata.
Inclusion of camera calibration parameters and MATLAB scripts for pose compensation.
Dataset covers eight scenes with varying biological sample representations.

Conclusions:

The presented dataset is a valuable resource for advancing volumetric reconstruction from FLMic images.
It enables rigorous testing and comparison of novel light field imaging algorithms.
Facilitates research in biological imaging and computational microscopy.