Accelerating DNA-PAINT imaging with a deep neural network
Authors/Creators
- 1. Heidelberg University
- 2. Goethe University Frankfurt
Description
(RawFrames_P5-IS_20pM.tif) Raw DNA-PAINT SMLM frames with isolated emitters taken on TOM20 labelled MNTB neuronal rat tissue with P5 imaging strand at 20 pM concentration.
(Binned_HighDensity_30kpatches.tif and Binned_HighDensity_30kpatches.csv) Artificially summed high-density emitter patches with the corresponding emitter coordinates used for training the DeepSTORM neural network.
(DeepSTORM_model_metadata.mat and DeepSTORM_model_weights_best.hdf5) The trained model metadata and weights used for all predicted images in the study.
(Figure 4_Large_super-resolution_image.png) The large super-resolution image in Figure 4 and Figure S4.
(High-density-frames_Images 1 - 5 .tif) Five high-emitter density raw frames for alpha-tubulin and TOM20 of 400 frames each.
(Ground-truth-rendered_Image 1 - 5.tif) Five ground truth images rendered in Picasso (drift-corrected, linked localisations, pixel size 13.37 nm/pixel) for alpha-tubulin and TOM20.
(Low density frames for GT images.zip) Five low-emitter density (0.5 nM) raw frames for alpha-tubulin and TOM20 of 10000 frames each which were used to render ground truth images.
(Bassoon_Homer_datasets.zip) Three Bassoon and Homer datasets each with a ground truth image and the corresponding high-density raw frames (5 nM, 800 frames).
Files
Bassoon_Homer_datasets.zip
Files
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