AIMD. AI for microscopy denoising - dataset 2

DOI

The dataset contains the second of two processed open-source datasets used in the Github repository: https://github.com/IPMI-ICNS-UKE/AIMD.AI-for-microscopy-denoising

The AIMD Github repository is demonstrating the use of open-source microscopy data for deep learning based image denoising and transfer learning as showcased in:  Lohr, D., Meyer, L., Woelk, LM., Kovacevic, D., Diercks, BP., Werner, R. (2025). Deep Learning-Based Image Restoration and Super-Resolution for Fluorescence Microscopy: Overview and Resources. In: Diercks, BP. (eds) T Cell Activation. Methods in Molecular Biology, vol 2904. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-4414-0_3

The original open-source data is from "Fluorescence Microscopy Datasets for Training Deep Neural Networks" - CC0 license     • http://gigadb.org/dataset/view/id/100888     • 16 bit image data, filetype: tif

Identifier
DOI https://doi.org/10.25592/uhhfdm.16914
Related Identifier IsPartOf https://doi.org/10.25592/uhhfdm.16913
Metadata Access https://www.fdr.uni-hamburg.de/oai2d?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:fdr.uni-hamburg.de:16914
Provenance
Creator Lohr, David ORCID logo; Werner, René ORCID logo
Publisher Universität Hamburg
Publication Year 2025
Rights Creative Commons Zero v1.0 Universal; Open Access; https://creativecommons.org/publicdomain/zero/1.0/legalcode; info:eu-repo/semantics/openAccess
OpenAccess true
Representation
Language English
Resource Type Dataset
Discipline Medicine