Join us for BioImage Informatics 2019, an annual meeting in the processing, analysis, and extraction of information and knowledge from biomedical images. This year's conference will take place at the Allen Institute from October 2-4, 2019, and will be organized by Mike Hawrylycz from the Allen Institute for Brain Science and Winfried Wiegraebe from the Allen Institute for Cell Science.
Advances in biological cell and tissue labeling and automated microscopy and imaging have revolutionized how biologists visualize molecular, cellular, and compartmental structures and study their respective functions. Huge volumes of multi-dimensional bioimaging data are now being generated in almost every branch of cell biology and neuroscience, particularly through dynamic imaging and electron microscopy applications. The interpretation and analysis of these image datasets in a quantitative, objective, automatic and efficient manor is a major challenge in current computational biology. The field of bioimage informatics also encompasses both hypothesis- and data-driven exploratory approaches, with an emphasis on how to generate biological knowledge and insights.
BioImage Informatics is an annual meeting in the processing, analysis, and extraction of information and knowledge from biomedical images. The meeting was established in 2005 and has met annually with key leaders in the field and an annual attendance of approximately 200 computational scientists. Previous meetings have been held in Banff 2017, Singapore 2016, NIST USA, 2015, Leuven Belgium, 2014, and Dresden, Germany 2012. The meeting has been influential in the field and is attended by strong researchers and students interested in this informatics domain. With the advent of machine learning applications in cellular resolution science, the significance of these tools and techniques is of increasing value.
BioImage Informatics 2019 meeting themes include:
Applications of machine and deep learning to analysis of cellular structure and related function
Reconstruction and analysis of neuronal structure and networks
Morphological image analysis and its contribution to cell type and cell state and creation of atlases
Quantification of dynamic images and transport phenomena
Automation of data acquisition and analysis
Dynamic cell imaging and biological processes