Comparison and practical review of segmentation approaches for label-free microscopy
This dataset contains microscopic images of PNT1A cell line captured by multiple microcopic without use of any labeling and a manually annotated ground truth for subsequent use in segmentation algorithms. Dataset also includes images reconstructed according to the methods described below in order to...
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Zenodo
2018
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Online Access: | https://dx.doi.org/10.5281/zenodo.1250729 https://zenodo.org/record/1250729 |
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ftdatacite:10.5281/zenodo.1250729 |
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record_format |
openpolar |
institution |
Open Polar |
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DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
unknown |
topic |
microscopy cell segmentation image reconstruction differential image quantitative phase imaging label-free |
spellingShingle |
microscopy cell segmentation image reconstruction differential image quantitative phase imaging label-free Tomas Vicar Balvan, Jan Slaby, Tomas Jaros, Josef Jug, Florian Kolar, Radim Masarik, Michal Gumulec, Jaromir Comparison and practical review of segmentation approaches for label-free microscopy |
topic_facet |
microscopy cell segmentation image reconstruction differential image quantitative phase imaging label-free |
description |
This dataset contains microscopic images of PNT1A cell line captured by multiple microcopic without use of any labeling and a manually annotated ground truth for subsequent use in segmentation algorithms. Dataset also includes images reconstructed according to the methods described below in order to ease further segmentation. See Vicar et al. Cell segmentation methods for label-free contrast microscopy: review and comprehensive comparison. BMC Bioinformatics (2019) 20:360. DOI 10.1186/s12859-019-2880-8 Code using this dataset is available at https://github.com/tomasvicar/Cell-segmentation-methods-comparison Materials and methods Cells were cultured in RPMI-1640 medium supplemented with antibiotics (penicillin 100 U/ml and streptomycin 0.1 mg/ml) with 10% fetal bovine serum. Prior microscopy acquisition, cells were maintained at 37 cenigrade in a humidified incubator with 5% CO2. Intentionally, high passage number of cells was used (>30) in order to describe distinct morphological heterogeneity of cells (rounded and spindle-shaped, relatively small to large polyploid cells). For acquisition purposes, cells were cultivated in Flow chambers µ-Slide I Luer Family (Ibidi, Martinsried, Germany). Quantitative phase imaging (QPI) microscopy was performed on Tescan Q-PHASE (Tescan, Brno, Czech republic), with objective Nikon CFI Plan Fluor 10x/0.30 captured by Ximea MR4021MC (Ximea, Münster, Germany). Imaging is based on the original concept of coherence-controlled holographic microscope \cite{Kolman:10,Slaby:13}, images are shown in grayscale with units of pg/µm2. DIC microscopy was performed on microscope Nikon A1R (Nikon, Tokyo, Japan), with objective Nikon CFI Plan Apo VC 20x/0.75 captured by CCD camera Jenoptik ProgRes MF (Jenoptik, Jena, Germany). HMC microscopy was performed on microscope Olympus IX71 (Olympus, Tokyo, Japan), with objective Olympus CplanFL N 10x/0.3 RC1 captured by CCD camera Hamamatsu Photonics ORCA-R2 (Hamamatsu Photonics K.K., Hamamatsu, Japan). PC microscopy was performed on a Nikon Eclipse TS100-F microscope, with a Nikon CFI Achro ADL 10x/0.25 objective captured by CCD camera Jenoptik ProgRes MF. Folder structure and file and filename description folder "source data+groundtruth" - includes raw microscopic data (uncompressed 16-bit for DIC, HMC and PC, 32-bit for QPI) - includes manualy annotated groundtruth (zip file - imageJ ROI file, 1bit png mask) e.g. DIC_01_raw.tif DIC_01_groundtruth_imagejROI.zip DIC_01_groundtruth_mask.png folder "reconstructions" includes reconstructed images using reconstructions with highest dice coefficient achieved. for DIC and HMC: rDIC-Koos, rDIC-Yin, and rWeka for PC: rPC-Top-Hat, rDIC-Yin, and rWeka for QPI: rWeka note that for rWeka images numbered 01 for DIC, HMC and PC and 01-03 for QPI were used for learning. Abbreviations DIC, differential image contrast HMC, Hoffman modulation contrast PC, phase contrast QPI, quantitative phase imaging rDIC-Koos, DIC/HMC image reconstruction according to Koos et al, Sci Rep. 2016;6:30420 rDIC-Yin, DIC/HMC image reconstruction according to Yin et al, Inf Process Med Imaging. 2011;22:384-97. rPC-Yin, PC image reconstruction according to Yin et al, Med Im Anal. 2012; 16(5):1047 rPC-Top-Hat, Top-Hat filter according to Dewan et al, IEEE Transactions on Biomedical Circuits and Systems.2014;8(5):716-728 rWeka, probability map using Trainable Weka segmentation according to Arganda-Carreras et al. Bioinformatics. 2017 : This work was supported by the Czech Science Foundation GACR 18-24089S : {"references": ["icar et al. Cell segmentation methods for label-free contrast microscopy: review and comprehensive comparison. BMC Bioinformatics (2019) 20:360. DOI\u00a010.1186/s12859-019-2880-8"]} |
format |
Dataset |
author |
Tomas Vicar Balvan, Jan Slaby, Tomas Jaros, Josef Jug, Florian Kolar, Radim Masarik, Michal Gumulec, Jaromir |
author_facet |
Tomas Vicar Balvan, Jan Slaby, Tomas Jaros, Josef Jug, Florian Kolar, Radim Masarik, Michal Gumulec, Jaromir |
author_sort |
Tomas Vicar |
title |
Comparison and practical review of segmentation approaches for label-free microscopy |
title_short |
Comparison and practical review of segmentation approaches for label-free microscopy |
title_full |
Comparison and practical review of segmentation approaches for label-free microscopy |
title_fullStr |
Comparison and practical review of segmentation approaches for label-free microscopy |
title_full_unstemmed |
Comparison and practical review of segmentation approaches for label-free microscopy |
title_sort |
comparison and practical review of segmentation approaches for label-free microscopy |
publisher |
Zenodo |
publishDate |
2018 |
url |
https://dx.doi.org/10.5281/zenodo.1250729 https://zenodo.org/record/1250729 |
long_lat |
ENVELOPE(156.767,156.767,-80.217,-80.217) |
geographic |
Olympus |
geographic_facet |
Olympus |
genre |
Orca |
genre_facet |
Orca |
op_relation |
https://github.com/tomasvicar/Cell-segmentation-methods-comparison https://github.com/tomasvicar/Cell-segmentation-methods-comparison https://dx.doi.org/10.1186/s12859-019-2880-8 https://dx.doi.org/10.5281/zenodo.1250728 |
op_rights |
Open Access Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 info:eu-repo/semantics/openAccess |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.5281/zenodo.1250729 https://doi.org/10.1186/s12859-019-2880-8 https://doi.org/10.5281/zenodo.1250728 |
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1766161786144292864 |
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ftdatacite:10.5281/zenodo.1250729 2023-05-15T17:54:04+02:00 Comparison and practical review of segmentation approaches for label-free microscopy Tomas Vicar Balvan, Jan Slaby, Tomas Jaros, Josef Jug, Florian Kolar, Radim Masarik, Michal Gumulec, Jaromir 2018 https://dx.doi.org/10.5281/zenodo.1250729 https://zenodo.org/record/1250729 unknown Zenodo https://github.com/tomasvicar/Cell-segmentation-methods-comparison https://github.com/tomasvicar/Cell-segmentation-methods-comparison https://dx.doi.org/10.1186/s12859-019-2880-8 https://dx.doi.org/10.5281/zenodo.1250728 Open Access Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 info:eu-repo/semantics/openAccess CC-BY microscopy cell segmentation image reconstruction differential image quantitative phase imaging label-free dataset Dataset 2018 ftdatacite https://doi.org/10.5281/zenodo.1250729 https://doi.org/10.1186/s12859-019-2880-8 https://doi.org/10.5281/zenodo.1250728 2021-11-05T12:55:41Z This dataset contains microscopic images of PNT1A cell line captured by multiple microcopic without use of any labeling and a manually annotated ground truth for subsequent use in segmentation algorithms. Dataset also includes images reconstructed according to the methods described below in order to ease further segmentation. See Vicar et al. Cell segmentation methods for label-free contrast microscopy: review and comprehensive comparison. BMC Bioinformatics (2019) 20:360. DOI 10.1186/s12859-019-2880-8 Code using this dataset is available at https://github.com/tomasvicar/Cell-segmentation-methods-comparison Materials and methods Cells were cultured in RPMI-1640 medium supplemented with antibiotics (penicillin 100 U/ml and streptomycin 0.1 mg/ml) with 10% fetal bovine serum. Prior microscopy acquisition, cells were maintained at 37 cenigrade in a humidified incubator with 5% CO2. Intentionally, high passage number of cells was used (>30) in order to describe distinct morphological heterogeneity of cells (rounded and spindle-shaped, relatively small to large polyploid cells). For acquisition purposes, cells were cultivated in Flow chambers µ-Slide I Luer Family (Ibidi, Martinsried, Germany). Quantitative phase imaging (QPI) microscopy was performed on Tescan Q-PHASE (Tescan, Brno, Czech republic), with objective Nikon CFI Plan Fluor 10x/0.30 captured by Ximea MR4021MC (Ximea, Münster, Germany). Imaging is based on the original concept of coherence-controlled holographic microscope \cite{Kolman:10,Slaby:13}, images are shown in grayscale with units of pg/µm2. DIC microscopy was performed on microscope Nikon A1R (Nikon, Tokyo, Japan), with objective Nikon CFI Plan Apo VC 20x/0.75 captured by CCD camera Jenoptik ProgRes MF (Jenoptik, Jena, Germany). HMC microscopy was performed on microscope Olympus IX71 (Olympus, Tokyo, Japan), with objective Olympus CplanFL N 10x/0.3 RC1 captured by CCD camera Hamamatsu Photonics ORCA-R2 (Hamamatsu Photonics K.K., Hamamatsu, Japan). PC microscopy was performed on a Nikon Eclipse TS100-F microscope, with a Nikon CFI Achro ADL 10x/0.25 objective captured by CCD camera Jenoptik ProgRes MF. Folder structure and file and filename description folder "source data+groundtruth" - includes raw microscopic data (uncompressed 16-bit for DIC, HMC and PC, 32-bit for QPI) - includes manualy annotated groundtruth (zip file - imageJ ROI file, 1bit png mask) e.g. DIC_01_raw.tif DIC_01_groundtruth_imagejROI.zip DIC_01_groundtruth_mask.png folder "reconstructions" includes reconstructed images using reconstructions with highest dice coefficient achieved. for DIC and HMC: rDIC-Koos, rDIC-Yin, and rWeka for PC: rPC-Top-Hat, rDIC-Yin, and rWeka for QPI: rWeka note that for rWeka images numbered 01 for DIC, HMC and PC and 01-03 for QPI were used for learning. Abbreviations DIC, differential image contrast HMC, Hoffman modulation contrast PC, phase contrast QPI, quantitative phase imaging rDIC-Koos, DIC/HMC image reconstruction according to Koos et al, Sci Rep. 2016;6:30420 rDIC-Yin, DIC/HMC image reconstruction according to Yin et al, Inf Process Med Imaging. 2011;22:384-97. rPC-Yin, PC image reconstruction according to Yin et al, Med Im Anal. 2012; 16(5):1047 rPC-Top-Hat, Top-Hat filter according to Dewan et al, IEEE Transactions on Biomedical Circuits and Systems.2014;8(5):716-728 rWeka, probability map using Trainable Weka segmentation according to Arganda-Carreras et al. Bioinformatics. 2017 : This work was supported by the Czech Science Foundation GACR 18-24089S : {"references": ["icar et al. Cell segmentation methods for label-free contrast microscopy: review and comprehensive comparison. BMC Bioinformatics (2019) 20:360. DOI\u00a010.1186/s12859-019-2880-8"]} Dataset Orca DataCite Metadata Store (German National Library of Science and Technology) Olympus ENVELOPE(156.767,156.767,-80.217,-80.217) |