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R Syntax - 5.9 KB - MD5: aedacc09bfa6ffabbe0f9c029864a811
The "Script.R" file contains all the required R commands to develop the main model described in the related publication
Plain Text - 30.0 MB - MD5: 7591534c20ec2d832f94a53bb7677f3c
The "Spectra.txt" file contains the reference spectral dataset, with columns named with their corresponding wavelength number (X350 to X2450) and the sample identifier ("Sample")
Plain Text - 10.6 KB - MD5: ed8103b3925e9bc9cfb0df4aa4d8794f
The "Values.txt" file contains the reference chemical values for d13C, d15N, C, N and the C/N ratios (with equivalent column names) as well as the sample identifier
Jun 25, 2021
Opstad, Ida S.; Godtliebsen, Gustav; Sekh, Arif Ahmed, 2021, "Replication Data for: Physics based machine learning for sub-cellular segmentation in living cells", https://doi.org/10.18710/IDCUCI, DataverseNO, V1
Abstract: Segmenting sub-cellular structures in living cells from fluorescence microscopy images is a ground truth (GT) hard problem. The microscope’s 3-dimensional blurring function, finite optical resolution due to light diffraction, finite pixel resolution, and complex morphological manifestations of the structures, all contribute to GT-hardness...
Plain Text - 15.6 KB - MD5: e132db0a0f357ed56600fb8b42da3583
TIFF Image - 2.2 GB - MD5: 029affcfecc6d103b8759f71573bb938
Microscopy image data for the dataset LiveEpi1Hu.
TIFF Image - 5.9 GB - MD5: 327545c1f25dec967b1d476214526cd0
Microscopy image data for the dataset LiveEpi1Hu.
TIFF Image - 2.3 GB - MD5: 7559de449111ab8e9aaaf981b4f8d928
Microscopy image data for the dataset LiveEpi1Hu.
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