EMPIAR-10592
CEM500K - A large-scale heterogeneous unlabeled cellular electron microscopy image dataset for deep learning. [496544 micrographs in TIFF format]
Publication:

CEM500K - A large-scale heterogeneous unlabeled cellular electron microscopy image dataset for deep learning.

Conrad RW, Narayan K

bioRxiv (2020)

Related EMDB entry:
Deposited:
2020-12-11
Released:
2020-12-21
Last modified:
2022-01-26
Imageset size:
16.61 GB
Imageset DOI:
Experimental metadata:
Download xml json
Contains:
  • micrographs - single frame
1. CEM500K
Category:
micrographs - single frame
Image format:
TIFF
No. of images or tilt series:
496544
Image size:
(224, 224)
Pixel type:
UNSIGNED BYTE
Pixel spacing:
(None, None)
Details:
CEM500K is a collection of 496,544 images (224x224 unsigned 8 bit .tiff) of cellular EM images, curated specifically for deep learning applications. See for more details: https://doi.org/10.1101/2020.12.11.421792

data/metadata/cem500k_image_metadata.csv file contains the details of each image file in CEM500K: image_name, source_experiment, doi, imaging_mode, organism, tissue

ResNet50 weights pretrained on CEM500K using MoCoV2 algorithm in PyTorch format are stored in data/pretrained_models/cem500k_mocov2_resnet50_200ep_pth.tar
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