Banca dati, 2023, ENG

Dataset ALFI: Cell cycle phenotype annotations of label-free time-lapse imaging data from cultured human cells

L. Antonelli, F. Polverino, A. Albu, A. Hada, I.A. Asteriti, F. Degrassi, G. Guarguaglini, L. Maddalena, M.R. Guarracino

ICAR, Institute for High-Performance Computing and Networking, National Research Council, Naples, Italy/ IBPM, Institute of Molecular Biology and Pathology, National Research Council, Rome, Italy/ Department of Economics and Law, University of Cassino and Southern Lazio, Cassino, Italy/ Laboratory of Algorithms and Technologies for Networks Analysis, National Research University Higher School of Economics, Moscow, Russia.

ALFI is a dataset of images and annotations for label-free microscopy, made publicly available to the scientific community, that notably extends the current panorama of expertly labeled data for detection and tracking of cultured living nontransformed and cancer human cells. It consists of 29 time-lapse image sequences from HeLa, U2OS, and hTERT RPE-1 cells under different experimental conditions, acquired by differential interference contrast microscopy, for a total of 237.9 hours. It contains various annotations (pixel-wise segmentation masks, object-wise bounding boxes, tracking information). The dataset is useful for testing and comparing methods for identifying interphase and mitotic events and reconstructing their lineage, and for discriminating different cellular phenotypes.

Keywords

ALFI dataset, label-free imaging, cell segmentation, event detection, tracking, lineage

CNR authors

Guarracino Mario Rosario, Maddalena Lucia, Antonelli Laura

CNR institutes

ICAR – Istituto di calcolo e reti ad alte prestazioni