January 31 Deadline for 2023 SABI Workshop Abstract Submission
Dear colleagues,
This is a reminder that abstract submission for the upcoming Spatial Analysis for Biological Imaging (SABI) Workshop is set to close on January 31, 2023. If you would like your work to be considered for presentation at the workshop, please submit your abstract before the deadline. Please also feel free to forward a copy of this email to colleagues who might be interested in this workshop.
Attendees of the workshop are encouraged to submit abstracts on their latest findings in relation to methods for spatial analysis (including spatial statistics, machine learning, and topological data analysis) and their applications in biomedical and clinical investigations. Please visit the following page to submit your abstract:
https://www.quantitativebioimaging.com/qbi2023/sabi2023/sabi-2023-abstract-submission/
Spatial Analysis for Biological Imaging is a two-day workshop to be held from Wednesday, March 29, 2023 to Thursday, March 30, 2023 at the Department of Mathematics, Imperial College London, South Kensington Campus, London. The workshop is hosted and supported by the Quantitative Sciences Research Institute, Imperial College London, in partnership with the QBI Society. To date, the following invited speakers have been confirmed:
- Carolina Wählby (Uppsala University)
- Dylan Owen (University of Birmingham)
- Thibault Lagache (Institut Pasteur)
- Anthea Monod (Imperial College London)
- Anca Grapa (Institute of Cancer Research, London)
- Daniel Davis (Imperial College London),
- Sripad Ram (Pfizer, San Diego)
- Susan Cox (King’s College London)
- Ed Cohen (Imperial College London)
Workshop Aim: Imaging technologies play an ever increasing role in biomedical and clinical investigations as they allow the observation of important spatial processes. While such imaging approaches have undergone major technological developments through, for example, the development of novel detectors and sample preparation approaches, the analysis of the resulting data has often lagged behind. This is even more problematic as the amount of data that can and is being generated is very large.
Methods for spatial analysis, including spatial statistics, machine learning, and topological data analysis, hold significant promise to be able to resolve many outstanding analytical problems. The purpose of this workshop is to provide a means for leading researchers in bioimaging, digital pathology and histology to present their latest findings and also to, for the first time, bring these communities together as it is expected that exchange of ideas could be of major benefit to all sides.
For more on this workshop, including registration, information about the venue, and a tentative schedule outline, please visit its official web page at
https://www.quantitativebioimaging.com/qbi2023/sabi2023/
We look forward to your abstract submission and seeing you at the workshop!
QBI Society