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CIVIT dataset: Integral microscopy with Fourier plane recording

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 ca...

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Detalles Bibliográficos
Autores principales: Moreschini, Sergio, Gama, Filipe, Bregovic, Robert, Gotchev, Atanas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9801074/
https://www.ncbi.nlm.nih.gov/pubmed/36591387
http://dx.doi.org/10.1016/j.dib.2022.108819
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author Moreschini, Sergio
Gama, Filipe
Bregovic, Robert
Gotchev, Atanas
author_facet Moreschini, Sergio
Gama, Filipe
Bregovic, Robert
Gotchev, Atanas
author_sort Moreschini, Sergio
collection PubMed
description 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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spelling pubmed-98010742022-12-31 CIVIT dataset: Integral microscopy with Fourier plane recording Moreschini, Sergio Gama, Filipe Bregovic, Robert Gotchev, Atanas Data Brief Data Article 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. Elsevier 2022-12-12 /pmc/articles/PMC9801074/ /pubmed/36591387 http://dx.doi.org/10.1016/j.dib.2022.108819 Text en © 2022 The Authors. Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Moreschini, Sergio
Gama, Filipe
Bregovic, Robert
Gotchev, Atanas
CIVIT dataset: Integral microscopy with Fourier plane recording
title CIVIT dataset: Integral microscopy with Fourier plane recording
title_full CIVIT dataset: Integral microscopy with Fourier plane recording
title_fullStr CIVIT dataset: Integral microscopy with Fourier plane recording
title_full_unstemmed CIVIT dataset: Integral microscopy with Fourier plane recording
title_short CIVIT dataset: Integral microscopy with Fourier plane recording
title_sort civit dataset: integral microscopy with fourier plane recording
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9801074/
https://www.ncbi.nlm.nih.gov/pubmed/36591387
http://dx.doi.org/10.1016/j.dib.2022.108819
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