UCSF

University of California San Francisco – Holographic Imaging Cytometry Center of Excellence

University of California, San Francisco (UCSF) and PHI have jointly created a regional Holographic Imaging Cytometry Center of Excellence headed by Dr. Robert Judson-Torres. Located at the UCSF Helen Diller Family Comprehensive Cancer Center, the Center’s activities focus on bringing the benefits of holographic cytometry and machine-learning to the UCSF research community, by providing education and technical support.

The recurring UCSF-PHI symposium serve as a forum for scientists who worldwide develop new therapies and diagnostic techniques for melanoma and other cancers.

The speakers at the UCSF-PHI symposium 2018.

“Holographic cytometry permits simultaneous quantification of cell division, death, senescence, and motility of adherent cells over long-term culture”

— Dr. Robert Judson-Torres
University of California, San Francisco

Dr. Robert Judson-Torres

Principal Investigator and a Sandler Fellow at the UCSF Department of Dermatology

Judson's research interests focus on the networks of genes and environmental factors that stabilize cell states in adult mammalian organisms, and, conversely, the coordinated sets of destabilizing factors which can lead to tumorigenesis. He is also actively involved with exploring new models of scientific training, communication and publication, including experimenting with forums for post-publication peer review, reproducibility initiatives, and strategies for training the scientific workforce.

Website: judsonlab.ucsf.edu

Peer Reviewed Articles and Book Chapters

  • SPIE Conference Proceedings, 2018 | M Hejna, A Jorapur, Y Zhang, J S Song and R L Judson

    Working with a HoloMonitor M4 digital holographic cytometry platform, we have established a machine learning-based pipeline for high accuracy and label-free classification of adherent cells.

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  • Nature Communications, 2017 | I. Yeh et al

    HoloMonitor was used to measure cell volume. Together with other methods the results identify DPN (deep penetrating nevus) as an intermediate melanocytic neoplasm, with a progression stage positioned between benign nevus and DPN-like melanoma.

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  • Scientific Reports, 2017 | M. Hejna

    The authors used machine learning to develop a method for robust and kinetic label-free classification of single adherent cells info functional states.

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Location

Helen Diller Family Comprehensive Cancer Center
1450 3rd St, San Francisco
CA 94158, USA