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Jun 25, 2021 - UiT The Arctic University of Norway
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.
TIFF Image - 600.3 MB - MD5: a367df01eaedc55932a7da00ae092620
Microscopy image data pertaining to the dataset LiveEpi1Hu.
TIFF Image - 9.8 GB - MD5: 5135ded869c654babcee5dadce1f590d
Microscopy image data for the dataset LiveEpi1Rat.
TIFF Image - 9.8 GB - MD5: ee34513de32896e9ab4cd892821bda19
Microscopy image data for the dataset LiveEpi1Rat.
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