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

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)

DOI: 10.1101/2020.12.11.421792

Related EMDB entry:

Deposited:

2020-12-11

Released:

2020-12-21

Last modified:

2022-01-26

Imageset size:

16.61 GB

Imageset DOI:

10.6019/EMPIAR-10592

Experimental metadata:

Download xml json

Contains:

micrographs - single frame

Image Sets

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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