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Imaging Level 4

An Imaging Level 4 entry describes derived imaging data in the form of an object-by-feature array — the quantitative output produced after segmented objects (e.g. cells) have had their features (e.g. per-channel marker intensities, morphology) extracted and summarized. Rather than image or mask files, this module captures tabular, analysis-ready data: the number of objects and features described, the object class involved, and the summary statistic (mean, median, or otherwise) used to aggregate feature values per object.

Imaging Level 4 entries reference the full processing lineage that produced them, linking back to the pre-processed image (ImagingLevel2 Key), the QC'd/co-registered image (ImagingLevel3Image Key), and the segmentation used (ImagingLevel3Segments Key). This level typically represents the final, most analysis-ready product of the imaging pipeline, suitable for downstream statistical or machine learning analyses.

Why You Should Contribute Imaging Level 4 Entries

Contributing Imaging Level 4 entries ensures that derived, object-level feature data is documented with a clear link back to the images and segmentations that produced it, making quantitative imaging results reusable and interpretable by other researchers.

Who Should Be Contributing Imaging Level 4 Entries?

  1. Computational Imaging Analysts – Document feature extraction pipelines and the resulting object-by-feature arrays.
  2. Imaging Scientists – Confirm that extracted features and summary statistics align with the biological question being addressed.
  3. Data Scientists – Ensure derived feature data is complete and well-annotated for downstream statistical or machine learning analyses.
  4. Data Managers – Track derived data files to maintain a complete record from raw image through to final quantitative output.

Download Template

You can download the ImagingLevel4 CSV template to streamline data entry.

Full Field Reference

Below is the full field reference table with attributes and their descriptions.

Attribute Description Required Column Type Format Regex Pattern Standard Terms Examples
ImagingLevel4_id Unique row identifier, used as a primary key for record updates. This should be equivalent to the file Synapse Id unless otherwise indicated. True string None ^syn\d{7,8}$ None
Filename The path of a file in Synapse, relative to the project. The file associated with the path will be annotated with attributes contained in this sheet. False string None None None
ImagingLevel2 Key Unique ImagingLevel2_id foreign key(s) that link metadata entries as part of the same Dataset. Please provide multiple values as a comma-separate list. False string None None None
ImagingLevel3Image Key Unique ImagingLevel3Image_id foreign key(s) that link metadata entries as part of the same Dataset. Please provide multiple values as a comma-separate list. False string None None None
ImagingLevel3Segments Key Unique ImagingLevel3Segments_id foreign key(s) that link metadata entries as part of the same Dataset. Please provide multiple values as a comma-separate list. False string None None None
Biospecimen Key Unique Biospecimen_id foreign key(s) that link metadata entries as part of the same collection. Please provide multiple values as a comma-separated list. False string None -B\d{1,9} None
Study Key The unique Study_id foreign keys associated with the resource, found in the grant Study information. Used to group the resource with other components. Please provide multiple values as a comma-separated list. False string None None None
DatasetView Key Unique DatasetView_id foreign key(s) that link metadata entries as part of the same collection. Please provide multiple values as a comma-separated list. False string None None None
File Alias A string identifier associated with the file. Must be unique. Can be the repository accesssion number (e.g., Synapse ID, GEO identifier such as GSE12345). No Greek Letters or DOIs. True string None None None
File Description Description of the file. False string None None None
File Design The overall design of the dataset or file, including a batch identifier, if applicable. False string None None None
File Level The processing level the file can be mapped to. True string None None View
File Assay The assay the file is representative of. True string None None View
File Species The species the data was collected on. True string None None View
File Url The url of where the file is stored. True string uri None None
File Format The format of the file described by this entry. True string None None View
File Data Use Codes DUO code - A data item that is used to indicate consent permissions for datasets and/or materials, and relates to the purposes for which datasets and/or material might be removed, stored or used. Available DUO code definitions can be found here: https://mc2-center.github.io/data-models/valid_values/study/#attribute-study-data-use-codes False string_list None None None
File Longitudinal Group A label that can be used to identify groups of files from the same longitudinal/time-resolved experiment False string None None None
File Longitudinal Event Type The type of event to which File Longitudinal Total Time Elapsed is related False string None None View
File Longitudinal Sequence Identifier The order in which this file was collected with respect to the longitudinal experiment (e.g., 1, 2, etc.). Integer. False number None None None
File Longitudinal Time Elapsed Unit The unit of time associated with Sequential and Total Time Elapsed attributes. False string None None None
File Longitudinal Total Time Elapsed The total time elapsed between the first and current files contained this longitudinal group. False number None None None
Image Parameter file Path in Synapse to a text file listing algorithm version numbers and relevant parameters needed to reproduce the analysis False string None None None
Image Software The name of the software package that was used to capture, generate, and process the image. False string None None None
Image Number of Objects The number of objects (eg cells) described False number None None None
Image Number of Features The number of features (eg channels) described True number None None None
Image Object Class Defines the structure that the mask delineates False string None None View
Image Summary Statistic Function used to summarize object/feature intensity True string None None View