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Image Search Results


Image acquisition produces primary raw image data along with the experimental parameters (cell seeding and gas plasma treatments) captured both during setup and during imaging, yet the associated metadata collection remains largely unstructured. Data are typically stored locally, annotated manually, and processed using analysis tools. The resulting datasets, often fragmented across files and folders, may create problems with sharing and archiving open repositories such as IDR and BIA. (X) Missing or manual data transfers; (?) Indicate uncertainties, such as incomplete metadata and unclear storage procedures. Created in BioRender. Bekeschus, S. (2026) https://BioRender.com/6tae47g .

Journal: bioRxiv

Article Title: Bioimaging Data Management Workflow for Plasma Medicine

doi: 10.64898/2026.01.26.700509

Figure Lengend Snippet: Image acquisition produces primary raw image data along with the experimental parameters (cell seeding and gas plasma treatments) captured both during setup and during imaging, yet the associated metadata collection remains largely unstructured. Data are typically stored locally, annotated manually, and processed using analysis tools. The resulting datasets, often fragmented across files and folders, may create problems with sharing and archiving open repositories such as IDR and BIA. (X) Missing or manual data transfers; (?) Indicate uncertainties, such as incomplete metadata and unclear storage procedures. Created in BioRender. Bekeschus, S. (2026) https://BioRender.com/6tae47g .

Article Snippet: After image annotation within the workflow, OMERO maps image acquisition metadata to the Open Microscopy Environment (OME) data model , translating file-specific parameters into a standardized structure.

Techniques: Clinical Proteomics, Imaging

The workflow is structured across three levels: metadata (Micro-Meta App, eLabFTW, and Adamant), data handling level (OMERO), and data processing level (annotation and analysis). Created in BioRender. Bekeschus, S. (2026) https://BioRender.com/1s1dfpy . A Jupyter notebook connecting all workflow components via Python scripts and user interfaces is available at https://github.com/INP-SDT/Bioimaging-Data-Management-Workflow-for-Plasma-Medicine .

Journal: bioRxiv

Article Title: Bioimaging Data Management Workflow for Plasma Medicine

doi: 10.64898/2026.01.26.700509

Figure Lengend Snippet: The workflow is structured across three levels: metadata (Micro-Meta App, eLabFTW, and Adamant), data handling level (OMERO), and data processing level (annotation and analysis). Created in BioRender. Bekeschus, S. (2026) https://BioRender.com/1s1dfpy . A Jupyter notebook connecting all workflow components via Python scripts and user interfaces is available at https://github.com/INP-SDT/Bioimaging-Data-Management-Workflow-for-Plasma-Medicine .

Article Snippet: After image annotation within the workflow, OMERO maps image acquisition metadata to the Open Microscopy Environment (OME) data model , translating file-specific parameters into a standardized structure.

Techniques: Clinical Proteomics

(i) microscopy images, (ii) microscope hardware and acquisition settings, and (iii) experimental records encompassing biological assays and gas plasma treatment. All collected metadata are systematically stored and linked in eLabFTW across imaging and experimental workflows. Created in BioRender. Bekeschus, S. (2026) https://BioRender.com/qlvnze6 .

Journal: bioRxiv

Article Title: Bioimaging Data Management Workflow for Plasma Medicine

doi: 10.64898/2026.01.26.700509

Figure Lengend Snippet: (i) microscopy images, (ii) microscope hardware and acquisition settings, and (iii) experimental records encompassing biological assays and gas plasma treatment. All collected metadata are systematically stored and linked in eLabFTW across imaging and experimental workflows. Created in BioRender. Bekeschus, S. (2026) https://BioRender.com/qlvnze6 .

Article Snippet: After image annotation within the workflow, OMERO maps image acquisition metadata to the Open Microscopy Environment (OME) data model , translating file-specific parameters into a standardized structure.

Techniques: Microscopy, Clinical Proteomics, Imaging

(Left) Schematic representation of the OMERO data hierarchy used in automation-assisted fluorescence imaging. Experiments are organized into “Screens” comprising one or more multi-well Plates. Each “Plate” consists of individual “Wells”, and each well may contain multiple image fields (illustrated as a 3 × 3 tiled acquisition), reflecting automated microscopy workflows. (Right) Exemplary metadata annotations associated with the OMERO hierarchy, shown as key–value pairs (KVPs). Metadata can be assigned at different hierarchical levels (Screen → Plate → Well → Image) and are directly linked to the corresponding image data within the workflow. Created in BioRender. Bekeschus, S. (2026) https://BioRender.com/whuauio .

Journal: bioRxiv

Article Title: Bioimaging Data Management Workflow for Plasma Medicine

doi: 10.64898/2026.01.26.700509

Figure Lengend Snippet: (Left) Schematic representation of the OMERO data hierarchy used in automation-assisted fluorescence imaging. Experiments are organized into “Screens” comprising one or more multi-well Plates. Each “Plate” consists of individual “Wells”, and each well may contain multiple image fields (illustrated as a 3 × 3 tiled acquisition), reflecting automated microscopy workflows. (Right) Exemplary metadata annotations associated with the OMERO hierarchy, shown as key–value pairs (KVPs). Metadata can be assigned at different hierarchical levels (Screen → Plate → Well → Image) and are directly linked to the corresponding image data within the workflow. Created in BioRender. Bekeschus, S. (2026) https://BioRender.com/whuauio .

Article Snippet: After image annotation within the workflow, OMERO maps image acquisition metadata to the Open Microscopy Environment (OME) data model , translating file-specific parameters into a standardized structure.

Techniques: Fluorescence, Imaging, Microscopy

(A) input field for specifying the “Screen” name to be annotated in OMERO, (B) input field for specifying the “Plate” name within the selected screen, (C) field for entering the eLabFTW experiment ID, which links the OMERO dataset to the metadata recorded in eLabFTW.

Journal: bioRxiv

Article Title: Bioimaging Data Management Workflow for Plasma Medicine

doi: 10.64898/2026.01.26.700509

Figure Lengend Snippet: (A) input field for specifying the “Screen” name to be annotated in OMERO, (B) input field for specifying the “Plate” name within the selected screen, (C) field for entering the eLabFTW experiment ID, which links the OMERO dataset to the metadata recorded in eLabFTW.

Article Snippet: After image annotation within the workflow, OMERO maps image acquisition metadata to the Open Microscopy Environment (OME) data model , translating file-specific parameters into a standardized structure.

Techniques:

(A) The OMERO interface displays an automation-assisted fluorescence imaging plate, including plate layout, well-level image previews, and a representative image field. Biological metadata associated with each well are shown in the metadata panel on the right, (B) An eLabFTW entry documenting the corresponding experimental procedure, linked resources, and attached JSON and CSV files that reference the imaging workflow, (C) The Adamant interface is used to define and validate the screen metadata schema. Full access to the dataset, including guiding documentation and all materials required to reproduce the example use case, is provided by INPTDAT at https://doi.org/10.34711/inptdat.1013 .

Journal: bioRxiv

Article Title: Bioimaging Data Management Workflow for Plasma Medicine

doi: 10.64898/2026.01.26.700509

Figure Lengend Snippet: (A) The OMERO interface displays an automation-assisted fluorescence imaging plate, including plate layout, well-level image previews, and a representative image field. Biological metadata associated with each well are shown in the metadata panel on the right, (B) An eLabFTW entry documenting the corresponding experimental procedure, linked resources, and attached JSON and CSV files that reference the imaging workflow, (C) The Adamant interface is used to define and validate the screen metadata schema. Full access to the dataset, including guiding documentation and all materials required to reproduce the example use case, is provided by INPTDAT at https://doi.org/10.34711/inptdat.1013 .

Article Snippet: After image annotation within the workflow, OMERO maps image acquisition metadata to the Open Microscopy Environment (OME) data model , translating file-specific parameters into a standardized structure.

Techniques: Fluorescence, Imaging

Journal: bioRxiv

Article Title: Bioimaging Data Management Workflow for Plasma Medicine

doi: 10.64898/2026.01.26.700509

Figure Lengend Snippet:

Article Snippet: After image annotation within the workflow, OMERO maps image acquisition metadata to the Open Microscopy Environment (OME) data model , translating file-specific parameters into a standardized structure.

Techniques: