CIVIT dataset: Integral microscopy with Fourier plane recording

Sergio Moreschini; Filipe Gama; Robert Bregovic; Atanas Gotchev

doi:10.1016/j.dib.2022.108819

CIVIT dataset: Integral microscopy with Fourier plane recording

Sergio Moreschini, Filipe Gama, Robert Bregovic, Atanas Gotchev

Computing Sciences

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Abstract

This article describes a dataset of synthetic images representing biological scenery as captured by a Fourier Lightfield Microscope (FLMic). It includes 22,416 images related to eight scenes composed of 3D models of objects typical for biological samples, such as red blood cells and bacteria, and categorized into Cells and Filaments groups. For each scene, two types of image data structures are provided: 51 × 51 Elemental Images (EIs) representing Densely Sampled Light Fields (DSLF) and 201 images composing Z-Scans of the scenes. Auxiliary data also includes information about camera intrinsic and extrinsic calibration parameters, object descriptions, and MATLAB scripts for camera pose compensation. The images have been generated using Blender. The dataset can be used to develop and assess methods for volumetric reconstruction from Light Field (LF) images captured by a FLMic.

Original language	English
Article number	108819
Journal	Data in Brief
Volume	46
Early online date	12 Dec 2022
DOIs	https://doi.org/10.1016/j.dib.2022.108819
Publication status	Published - Feb 2023
Publication type	A1 Journal article-refereed

Keywords

Fourier Lightfield Microscopy
Light Field
Blender
Z-Scan
Z-Stack
Cells
Filaments

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Publication forum level 1

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10.1016/j.dib.2022.108819Licence: CC BY

1-s2.0-S2352340922010228-mainFinal published version, 783 KBLicence: CC BY

https://urn.fi/URN:NBN:fi:tuni-202212239774Licence: CC BY

CIVIT Dataset: Integral Microscopy with Fourier Plane Recording
Moreschini, S. (Creator), Da Graca Gama, F. (Contributor), Bregovic, R. (Contributor) & Gotchev, A. (Contributor), 11 Nov 2022
DOI: 10.17632/22z5yhn928.2
Dataset

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title = "CIVIT dataset: Integral microscopy with Fourier plane recording",

abstract = "This article describes a dataset of synthetic images representing biological scenery as captured by a Fourier Lightfield Microscope (FLMic). It includes 22,416 images related to eight scenes composed of 3D models of objects typical for biological samples, such as red blood cells and bacteria, and categorized into Cells and Filaments groups. For each scene, two types of image data structures are provided: 51 × 51 Elemental Images (EIs) representing Densely Sampled Light Fields (DSLF) and 201 images composing Z-Scans of the scenes. Auxiliary data also includes information about camera intrinsic and extrinsic calibration parameters, object descriptions, and MATLAB scripts for camera pose compensation. The images have been generated using Blender. The dataset can be used to develop and assess methods for volumetric reconstruction from Light Field (LF) images captured by a FLMic.",

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author = "Sergio Moreschini and Filipe Gama and Robert Bregovic and Atanas Gotchev",

year = "2023",

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doi = "10.1016/j.dib.2022.108819",

language = "English",

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journal = "Data in Brief",

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T2 - Integral microscopy with Fourier plane recording

AU - Moreschini, Sergio

AU - Gama, Filipe

AU - Bregovic, Robert

AU - Gotchev, Atanas

PY - 2023/2

Y1 - 2023/2

N2 - This article describes a dataset of synthetic images representing biological scenery as captured by a Fourier Lightfield Microscope (FLMic). It includes 22,416 images related to eight scenes composed of 3D models of objects typical for biological samples, such as red blood cells and bacteria, and categorized into Cells and Filaments groups. For each scene, two types of image data structures are provided: 51 × 51 Elemental Images (EIs) representing Densely Sampled Light Fields (DSLF) and 201 images composing Z-Scans of the scenes. Auxiliary data also includes information about camera intrinsic and extrinsic calibration parameters, object descriptions, and MATLAB scripts for camera pose compensation. The images have been generated using Blender. The dataset can be used to develop and assess methods for volumetric reconstruction from Light Field (LF) images captured by a FLMic.

AB - This article describes a dataset of synthetic images representing biological scenery as captured by a Fourier Lightfield Microscope (FLMic). It includes 22,416 images related to eight scenes composed of 3D models of objects typical for biological samples, such as red blood cells and bacteria, and categorized into Cells and Filaments groups. For each scene, two types of image data structures are provided: 51 × 51 Elemental Images (EIs) representing Densely Sampled Light Fields (DSLF) and 201 images composing Z-Scans of the scenes. Auxiliary data also includes information about camera intrinsic and extrinsic calibration parameters, object descriptions, and MATLAB scripts for camera pose compensation. The images have been generated using Blender. The dataset can be used to develop and assess methods for volumetric reconstruction from Light Field (LF) images captured by a FLMic.

KW - Fourier Lightfield Microscopy

KW - Light Field

KW - Blender

KW - Z-Scan

KW - Z-Stack

KW - Cells

KW - Filaments

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DO - 10.1016/j.dib.2022.108819

M3 - Data article

SN - 2352-3409

VL - 46

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JF - Data in Brief

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ER -

CIVIT dataset: Integral microscopy with Fourier plane recording

Abstract

Keywords

Publication forum classification

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CIVIT Dataset: Integral Microscopy with Fourier Plane Recording

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