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Title: Fluorescence Reconstruction Microscopy: Complete Testing Dataset
Contributors: LaChance, Julienne
Cohen, Daniel
Keywords: machine learning
fluorescence reconstruction
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.
Appears in Collections:MAE Research Data Sets

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DataSpace_Full_Data_Details_README.pdfREADME documentation for the dataset62.38 kBAdobe PDFView/Download

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