All data sets used in the paper, along with the labels, can be downloaded from zenodo
This data set is obtaind from [1], which can be downloaded at https://www.zenodo.org/record/215600#.XK0LBJhKjBV.
We save the 20 images used in MATLAB file Bass.mat
. Inside that file, the 3D images are saved in cell array img3DLst
. The mean-projected 2D images are saved in cell array imgLst
. The 2D annotations are saved in annoMapLst
.
This data is obtained from [2], which can be downloaded at https://neurodata.io/data/collman15/.
We save Collman 14 and Collman 15 in Collman_clean.mat
. The annotations in EM channel that does not correspond to any fluorescence staining are removed. The images are saved in imgLst
. The first element of it is Collman 14
and the second is Collman 15
. Each is a 4D array (Height x Width by Depth by channel). The first chanenl is pre-synaptic and the second is post-synaptic. The 3D annotations from EM channel are saved in annoMapLst
. The first element is for Collman14
and the second is for Collman15
. Each is a 3D array (Height x Width x Depth).
This data is obtained from experiments performed in [3]. We save the data in guilai_ctrl_1_strong_high.mat
.
The 16 images are save in imgLst
where each element is a 2D image. The annotations are saved in annoMapLst
.
We generate synthetic data with three noise levels and three ranges of puncta sizes. There are 9 (3x3) experiment conditions in all. Each condition is saved in an individual .mat
file in folder synthetic
. The code to generate the data is prep_synthetic.m
.
Data | Min size (pixel) | Max size (pixel) | Average SNR |
---|---|---|---|
synthetic_smax_16_var1_0.0004.mat | 9 | 16 | 23.8 |
synthetic_smax_16_var1_0.0025.mat | 9 | 16 | 17.2 |
synthetic_smax_16_var1_0.01.mat | 9 | 16 | 11.5 |
synthetic_smax_50_var1_0.0004.mat | 9 | 50 | 23.8 |
synthetic_smax_50_var1_0.0025.mat | 9 | 50 | 17.2 |
synthetic_smax_50_var1_0.01.mat | 9 | 50 | 11.5 |
synthetic_smax_150_var1_0.0004.mat | 9 | 150 | 23.8 |
synthetic_smax_150_var1_0.0025.mat | 9 | 150 | 17.2 |
synthetic_smax_150_var1_0.01.mat | 9 | 150 | 11.5 |
In each .mat
file, imgLst
contains 10 images and annoMapLst
contains the ground truth labels.
[1] Bass, Cher, et al. "Detection of axonal synapses in 3d two-photon images." PloS one 12.9 (2017): e0183309.
[2] Collman, Forrest, et al. "Mapping synapses by conjugate light-electron array tomography." Journal of Neuroscience 35.14 (2015): 5792-5807.
[3] Mizuno, Grace O., et al. "Aberrant calcium signaling in astrocytes inhibits neuronal excitability in a human Down syndrome stem cell model." Cell reports 24.2 (2018): 355-365.