Leading Organizers¶
Jun Ma (University of Toronto)
Ronald Xie (University of Toronto)
Gary D. Bader (University of Toronto)
Bo Wang (University of Toronto)
Coordinators¶
(Clean data and contribute labeled images; beta testers; manage registrations; evaluate submissions)
José Guilherme de Almeida (European Bioinformatics Institute)
Shamini Ayyadhury (University of Toronto)
Sweta Banerjee (Indraprastha Institute of Information Technology-Delhi)
Leon Espinosa (CNRS-Aix-Marseille University)
Cheng Ge (Jiangsu University of Technology)
Song Gu (Nanjing Anke Medical Technology Co., Ltd.)
Anubha Gupta (Indraprastha Institute of Information Technology-Delhi)
Ritu Gupta (Institute Rotary Cancer Hospital of All India Institute of Medical Sciences)
Lin Han (New York University)
Marco Labagnara (École Polytechnique Fédérale de Lausanne)
Tâm Mignot (CNRS-Aix-Marseille University)
Sahand Jamal Rahi (École Polytechnique Fédérale de Lausanne)
Yixin Wang (Stanford University)
Xin Yang (Shenzhen University)
Yao Zhang (Institute of Computing Technology, Chinese Academy of Sciences; University of Chinese Academy of Sciences)
Data Contributors¶
We thank all the great data contributors to share their valuable microscopy images with this competition.
Yeast brightfield and phase-contrast images: Marco Labagnara, Sahand Jamal Rahi (École Polytechnique Fédérale de Lausanne)
U2OS and adipocyte fluorescent images: Patrick Byrne, Maria Alimova, Erin Weisbart, Beth Cimini, Shantanu Singh, Anne Carpenter (Broad Institute)
Multiple myeloma brightfield images: Sweta Banerjee, Anubha Gupta (Indraprastha Institute of Information Technology-Delhi); Ritu Gupta (Institute Rotary Cancer Hospital of All India Institute of Medical Sciences)
Brain cell phase-contrast images: Shamini Ayyadhury (University of Toronto)
Bone marrow smears (brightfield images): Jan Moritz Middeke, Jan-Niklas Eckardt (Technical University Dresden)
Bacteria brightfield and phase-contrast image: Leon Espinosa, Tâm Mignot (CNRS-Aix-Marseille University)
Peripheral blood smears (brightfield images): José Guilherme de Almeida (European Bioinformatics Institute)
Bone marrow slide (brightfield images): Oscar Brück (University of Helsinki)
Human adenoid and tonsil FFPE samples (fluorescent images): Andrea J. Radtke, Ronald N. Germain (National Institute of Allergy and Infectious Diseases (NIAID, NIH))
The following public images are used in this competition based on license permits or authors' approval.
Laura Capolupo. (2022). Digital Phase Contrast on Primary Dermal Human Fibroblasts cells (Version v0) [Data set].
https://zenodo.org/record/5996883
Kempster, Carly, et al.
"Fully automated platelet differential interference
contrast image analysis via deep learning." Scientific
reports 12.1 (2022):
1-13.https://researchdata.reading.ac.uk/332/
Bunk, David, et al. "YeastMate: neural network-assisted segmentation of
mating and budding events in Saccharomyces cerevisiae."
Bioinformatics 38.9 (2022): 2667-2669.
https://osf.io/287fr/
Dietler, Nicola, et al.
"A convolutional neural network segments yeast microscopy
images with high accuracy." Nature communications 11.1 (2020):
1-8.
https://www.epfl.ch/labs/lpbs/data-and-software/
Eckardt, Jan-Niklas, et al. "Deep learning detects acute myeloid leukemia and predicts NPM1 mutation status from bone marrow smears." Leukemia 36.1 (2022): 111-118.
https://www.kaggle.com/datasets/sebastianriechert/bone-marrow-slides-for-leukemia-prediction
Greenwald, Noah F., et al. "Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning." Nature biotechnology 40.4 (2022): 555-565.
https://datasets.deepcell.org/
Burri, Olivier, & Guiet, Romain. (2019). DAPI and Phase Contrast Images Dataset [Data set]. Zenodo.
https://doi.org/10.5281/zenodo.3232478
Ogawa, Taisaku, et al. "Different cell imaging methods did not significantly improve immune cell image classification performance." PloS one 17.1 (2022): e0262397.https://figshare.com/articles/dataset/Minimum_dataset_for_Different_cell_imaging_methods_did_not_significantly_improve_immune_cell_image_classification_performance_/14789811
Risom, Tyler, et al. "Transition to invasive breast cancer is associated with progressive changes in the structure and composition of tumor stroma." Cell 185.2 (2022): 299-310.
https://data.mendeley.com/datasets/d87vg86zd8/3
WangLab¶
BaderLab¶
SBILab¶
Mignot Lab¶
Acknowledgment¶
We thank all the coordinators and data contributors for their great contribution to this competition. Anubha Gupta and Sweta Banerjee would like to thank the Infosys Centre for AI, IIIT-Delhi for support in running this challenge. Anubha Gupta would also like to thank the Department of Science and Technology, Govt. of India for the SERB-POWER fellowship (Grant No.: SPF/2021/000209) to carry out this work.