Cargando…
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...
Autores principales: | , , , |
---|---|
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 |
_version_ | 1784861421275709440 |
---|---|
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. |
format | Online Article Text |
id | pubmed-9801074 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT moreschinisergio civitdatasetintegralmicroscopywithfourierplanerecording AT gamafilipe civitdatasetintegralmicroscopywithfourierplanerecording AT bregovicrobert civitdatasetintegralmicroscopywithfourierplanerecording AT gotchevatanas civitdatasetintegralmicroscopywithfourierplanerecording |