REL
2022-04-28
2022-05-20
2022-05-20
CEM1.5M : a cellular EM dataset containing ~1.5 x 106 unlabeled 2D image patches curated for deep learning
0000-0001-7982-6494
Kedar
Narayan
NCI/FNLCR
Frederick
MD
United States
21701
0000-0001-7982-6494
Kedar
Narayan
NCI/FNLCR
Frederick
MD
United States
21701
Narayan K
57.6
10.6019/EMPIAR-11035
FIB-SEM
Narayan K
Instance segmentation of mitochondria in electron microscopy images with a generalist deep learning model
EMPIAR-11037
1,592,753 unlabeled 2D cellular EM (CEM1.5M) image dataset curated for deep learning
/data
micrographs - single frame
TIFF
TIFF
1592753
1
UNSIGNED BYTE
224
variable
224
variable
This zip file contains 1,592,753 heterogeneous, information-rich, non-redundant unlabeled 2D cellular EM (hence CEM1.5M) images, divided into 651 subdirectories (each directory being a unique vEM or EM image set). The image patches are mostly 224 x 224 pixels, however some are 512 x 512, and some are smaller. The raw image data was curated for deep learning largely following Conrad and Narayan, eLife 2021. https://elifesciences.org/articles/65894