Please use this identifier to cite or link to this item:
http://arks.princeton.edu/ark:/88435/dsp013r074x85b
Title: | Fluorescence Reconstruction Microscopy: Complete Testing Dataset |
Contributors: | LaChance, Julienne Cohen, Daniel |
Keywords: | machine learning training fluorescence reconstruction FRM |
Issue Date: | Apr-2020 |
Publisher: | Princeton University |
Abstract: | We provide all the test data and corresponding predictions for our paper, “Practical Fluorescence Reconstruction Microscopy for High-Content Imaging”. Please refer to the Methods section in this paper for experimental details. For each experimental condition, we provide the input transmitted-light images (either phase contrast or DIC), the ground truth fluorescence images, and the output predicted fluorescence images which should reconstruct the ground truth fluorescence images. |
URI: | http://arks.princeton.edu/ark:/88435/dsp013r074x85b https://www.dropbox.com/sh/l3jb5ts6iow4daj/AAC_AaEAPykInyhFxG3fINdva?dl=0 https://www.dropbox.com/sh/2r2qm0awr8pahlr/AAAsvBvMtJPX_nqKyaodvuBZa?dl=0 https://www.dropbox.com/sh/g0kby5n93ftul0j/AADpLa5vhlJZIwXIgm9lpG_Wa?dl=0 https://www.dropbox.com/sh/l1d1eirhybmwtx0/AADJU3ZV1JKP6QNqX2jQJ0aba?dl=0 https://doi.org/10.34770/s59n-wm23 |
Appears in Collections: | MAE Research Data Sets |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
DataSpace_Full_Data_Details_README.pdf | README documentation for the dataset | 62.38 kB | Adobe PDF | View/Download |
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