Recently added (10)#

Axioscan 7 fluorescent channels not displaying in QuPath#

j

Published 2024-06-25

Hi @ome team,Please find the .czi file attached. When loaded into QuPath using BioFormats, the fluorescence channels populate the brightness/contrast panel but do not show up in the viewer. Re-exporting as OME.Tiff from Zen and loading into QuPath does not help either - the channels do not populate the brightness/contrast panel in this case, and it shows as a RGB image.Please let me know if any further info is needed from me to troubleshoot! Best,J

https://zenodo.org/records/12533989

https://doi.org/10.5281/zenodo.12533989


Cellpose model for Digital Phase Contrast images#

Laura Capolupo, Olivier Burri, Romain Guiet

Published 2022-02-09

Licensed CC-BY-4.0

Name: Cellpose model for Digital Phase Contrast images

Data type: Cellpose model, trained via transfer learning from ‘cyto’ model.

Training Dataset: Light microscopy (Digital Phase Contrast) and Manual annotations (10.5281/zenodo.5996883)

Training Procedure: Model was trained using a Cellpose version 0.6.5 with GPU support (NVIDIA GeForce RTX 2080) using default settings as per the Cellpose documentation 

python -m cellpose –train –dir TRAINING/DATASET/PATH/train –test_dir TRAINING/DATASET/PATH/test –pretrained_model cyto –chan 0 –chan2 0

The model file (MODEL NAME) in this repository is the result of this training.

Prediction Procedure: Using this model, a label image can be obtained from new unseen images in a given folder with

python -m cellpose –dir NEW/DATASET/PATH –pretrained_model FULL_MODEL_PATH –chan 0 –chan2 0 –save_tif –no_npy

https://zenodo.org/records/6023317

https://doi.org/10.5281/zenodo.6023317


Deconvolution Test Dataset#

Romain Guiet

Published 2021-07-14

Licensed CC-BY-4.0

This a test dataset, HeLa cells stained for action using Phalloidin-488 acquired on confocal Zeiss LSM710, which contains

  • Ph488.czi (contains all raw metadata)

  • Raw_large.tif ( is the tif version of Ph488.czi, provided for conveninence as tif doesn’t need Bio-Formats to be open in Fiji )

  • Raw.tif , is a crop of the large image

- PSFHuygens_confocal_Theopsf.tif , is a theoretical PSF generated with HuygensPro

- PSFgen_WF_WBpsf.tif  , is a theoretical PSF generated with PSF generator

  • PSFgen_WFsquare_WBpsf.tif, is the result of the square operation on PSFgen_WF_WBpsf.tif , to approximate a confocal PSF

https://zenodo.org/records/5101351

https://doi.org/10.5281/zenodo.5101351


Engineering a Software Environment for Research Data Management of Microscopy Image Data in a Core Facility#

Kunis

Published 2022-05-30

This thesis deals with concepts and solutions in the field of data management in everyday scientific life for image data from microscopy. The focus of the formulated requirements has so far been on published data, which represent only a small subset of the data generated in the scientific process. More and more, everyday research data are moving into the focus of the principles for the management of research data that were formulated early on (FAIR-principles). The adequate management of this mostly multimodal data is a real challenge in terms of its heterogeneity and scope. There is a lack of standardised and established workflows and also the software solutions available so far do not adequately reflect the special requirements of this area. However, the success of any data management process depends heavily on the degree of integration into the daily work routine. Data management must, as far as possible, fit seamlessly into this process. Microscopy data in the scientific process is embedded in pre-processing, which consists of preparatory laboratory work and the analytical evaluation of the microscopy data. In terms of volume, the image data often form the largest part of data generated within this entire research process. In this paper, we focus on concepts and techniques related to the handling and description of this image data and address the necessary basics. The aim is to improve the embedding of the existing data management solution for image data (OMERO) into the everyday scientific work. For this purpose, two independent software extensions for OMERO were implemented within the framework of this thesis: OpenLink and MDEmic. OpenLink simplifies the access to the data stored in the integrated repository in order to feed them into established workflows for further evaluations and enables not only the internal but also the external exchange of data without weakening the advantages of the data repository. The focus of the second implemented software solution, MDEmic, is on the capturing of relevant metadata for microscopy. Through the extended metadata collection, a corresponding linking of the multimodal data by means of a unique description and the corresponding semantic background is aimed at. The configurability of MDEmic is designed to address the currently very dynamic development of underlying concepts and formats. The main goal of MDEmic is to minimise the workload and to automate processes. This provides the scientist with a tool to handle this complex and extensive task of metadata acquisition for microscopic data in a simple way. With the help of the software, semantic and syntactic standardisation can take place without the scientist having to deal with the technical concepts. The generated metadata descriptions are automatically integrated into the image repository and, at the same time, can be transferred by the scientists into formats that are needed when publishing the data.

https://zenodo.org/records/6905931

https://doi.org/10.5281/zenodo.6905931


Evident OIR sample files with lambda scan - FV 4000#

Nicolas Chiaruttini

Published 2024-07-18

Licensed CC-BY-4.0

The files contained in this repository are confocal images taken with the Evident FV 4000 of a sample containing DAPI and mCherry stains, excited with the 405 nm laser and images for different emission windows (lambda scan). They are public sample files which goal is to help test edge cases of the bio-formats library (https://www.openmicroscopy.org/bio-formats/), in particular for the proper handling of lambda scans.

DAPI_mCherry_22Lambda-420-630-w10nm-s10nm.oir : 22 planes, each plane is an emission window, starting from 420 nm up to 630 nm by steps of 10 nm DAPI_mCherry_4T_5Lambda-420-630-w10nm-s50nm.oir : 20 planes, 5 lambdas from 420 to 630 nm by steps of 50 nm, 4 timepoints DAPI_mCherry_4Z_5Lambda-420-630-w10nm-s50nm.oir : 20 planes, 5 lambdas from 420 to 630 nm by steps of 50 nm, 4 slices DAPI-mCherry_3T_4Z_5Lambda-420-630-w10nm-s50nm.oir : 60 planes, 5 lambdas from 420 to 630 nm by steps of 50 nm, 4 slices, 3 timepoints

https://zenodo.org/records/12773657

https://doi.org/10.5281/zenodo.12773657


Human DAB staining Axioscan BF 20x#

Mario Garcia

Published 2024-05-21

Licensed CC-BY-4.0

Human brain tissue with DAB immunostaining. Image acquired by BF microscopy in  Zeiss Axioscan at 20x. 

https://zenodo.org/records/11234863

https://doi.org/10.5281/zenodo.11234863


ICS/IDS stitched file#

IMCF

Published 2024-06-13

Licensed CC-BY-4.0

Hi @ome team ! We usually use ICS/IDS file formats as an output to our stitching pipeline as the reading and writing is pretty fast. However, it seems that since Bio-Formats 7.x opening the files is not working anymore. I tried with a Fiji with Bio-Formats 6.10.1 and the files open, but more recent versions give an issue.   java.lang.NullPointerException at loci.formats.in.ICSReader.initFile(ICSReader.java:1481) at loci.formats.FormatReader.setId(FormatReader.java:1480) at loci.plugins.in.ImportProcess.initializeFile(ImportProcess.java:498) at loci.plugins.in.ImportProcess.execute(ImportProcess.java:141) at loci.plugins.in.Importer.showDialogs(Importer.java:156) at loci.plugins.in.Importer.run(Importer.java:77) at loci.plugins.LociImporter.run(LociImporter.java:78) at ij.IJ.runUserPlugIn(IJ.java:244) at ij.IJ.runPlugIn(IJ.java:210) at ij.Executer.runCommand(Executer.java:152) at ij.Executer.run(Executer.java:70) at ij.IJ.run(IJ.java:326) at ij.IJ.run(IJ.java:337) at ij.macro.Functions.doRun(Functions.java:703) at ij.macro.Functions.doFunction(Functions.java:99) at ij.macro.Interpreter.doStatement(Interpreter.java:281) at ij.macro.Interpreter.doStatements(Interpreter.java:267) at ij.macro.Interpreter.run(Interpreter.java:163) at ij.macro.Interpreter.run(Interpreter.java:93) at ij.macro.MacroRunner.run(MacroRunner.java:146) at java.lang.Thread.run(Thread.java:750)

You can find one example file at this link 1. Thanks for your help !Best,Laurent

https://zenodo.org/records/11637422

https://doi.org/10.5281/zenodo.11637422


Ink in a dish#

Cavanagh

Published 2024-09-03

Licensed CC-ZERO

A test data set for troublshooting. no scientific meaning.

https://zenodo.org/records/13642395

https://doi.org/10.5281/zenodo.13642395


LauLauThom/MaskFromRois-Fiji: Masks from ROIs plugins for Fiji - initial release#

Laurent Thomas, Pierre Trehin

Published 2021-07-22

Licensed MIT

Fiji plugins for the creation of binary and semantic masks from ROIs in the RoiManager. Works with stacks too.

Installation in Fiji: activate the Rois from masks update site in Fiji.

See GitHub readme for the documentation.

Latest tested with Fiji 2.1.0/ImageJ 1.53j

https://zenodo.org/records/5121890

https://doi.org/10.5281/zenodo.5121890


Structuring of Data and Metadata in Bioimaging: Concepts and technical Solutions in the Context of Linked Data#

Sarah Weischer, Jens Wendt, Thomas Zobel

Published 2022-07-12

Licensed CC-BY-4.0

Provides an overview of contexts, frameworks, and models from the world of bioimage data as well as metadata. Visualizes the techniques for structuring this data as Linked Data. (Walkthrough Video: https://doi.org/10.5281/zenodo.7018928 )

Content:

Types of metadata
Data formats
Data Models Microscopy Data
Tools to edit/gather metadata
ISA Framework
FDO Framework
Ontology
RDF
JSON-LD
SPARQL
Knowledge Graph
Linked Data
Smart Data
...

https://zenodo.org/records/7018750

https://doi.org/10.5281/zenodo.7018750