TRD 3 Resources
Open Source Technology
- SLAM weakly supervised cancer biomarker discovery
- Paper: Biomedical Optics Express, https://doi.org/10.1364/BOE.480687
- GitHub page: https://github.com/Biophotonics-COMI/MM-MIL
- Publication date: March 2023
- Code status: public
- MITO hyperspectral CARS weakly supervised drug fingerprint discovery
- Paper: Analytical Chemistry, https://doi.org/10.1021/acs.analchem.3c00979
- GitHub page: https://github.com/Biophotonics-COMI/HAN
- Publication date: July 2023
- Code status: public
- Biopharm single-cell analysis pipeline using SLAM and FLIM
- Paper: manuscript submitted, presented at SPIE PW 2024
- GitHub page: https://github.com/Biophotonics- COMI/Biopharm_cell_line_selection
- Code status: public (UIUC OTM license included)
- Self-supervised FLIM restoration
- Paper: manuscript under preparation, presented at SPIE PW 2024
- GitHub page: https://github.com/Biophotonics-COMI/DeepFLR
- Code status: private (will be public with OTM license when the manuscript is submitted)
- EVATOM: an optical, label-free, machine learning assisted embryo health assessment tool
- Paper: Communications Biology, https://doi.org/10.1038/s42003-024-05960-w
- GitHub page: https://github.com/NehaRG-QPI/embryo_ls_glim
- Publication date: March 2024
- Code status: public
- Semi-supervised semantic segmentation of cell nuclei with diffusion model and collaborative learning
- Paper: Journal of Medical Imaging, https://doi.org/10.1117/1.JMI.12.6.061403
- GitHub page: https://github.com/zhuchens-uiuc/DTSeg
- Publication date: March 2025
- Code status: public
- An Omni-Mesoscope for multiscale high-throughput quantitative phase imaging of cellular dynamics and high-content molecular characterization
- Paper: Science Advances, https://doi.org/10.1101/2024.07.18.604137
- Data Resource page: https://doi.org/10.5061/dryad.t76hdr88t
- Publication date: October 2024
- Code status: public
- A multi-modal whole-slide image processing pipeline for quantitative mapping of tissue architecture, histopathology, and tissue microenvironment
- Paper: bioRxiv, https://doi.org/10.1101/2025.03.05.641761
(manuscript submitted to npj Imaging, under review)
- GitHub page: https://github.com/YangLiuLab/MM_WS
- Publication date: March 2025
- Code status: public
- Paper: bioRxiv, https://doi.org/10.1101/2025.03.05.641761
Data Sharing
Realizations from Stochastic Image Models of Some Features Seen in Fluorescence Microscopy
https://doi.org/10.13012/B2IDB-2642688_V1
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Dataset Description |
8-bit RGB realizations of a stochastic image model (SIM) of the **kinds** of things seen in fluorescence microscopy of biological samples. Note that no attempt was made to model a particular tissue, sample, or microscope. Distinct image features are seen in each color channel. The first public mention of these SIMs is in "Evaluation of Machine-generated Biomedical Images via A Tally-based Similarity Measure" by Frank Brooks and Rucha Deshpande. Manuscript on ArXiv and submitted for publication. |
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Keywords |
image models; fluorescence microscopy; training data; image-to-image translation; generative model evaluation |
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License |
See license.txt file in dataset. |
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Funder |
U.S. National Institutes of Health (NIH)-Grant:P41EB031772 |
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Corresponding Creator |
Frank Brooks |