Workshop details
Date: Saturday September 3, 2016
Time: 9:00 – 17:00
Venue: World Forum, room: Everest 2
Workshop website
Keydates
Organisers
- Yves Sucaet, Vrije Universiteit Brussel, Belgium
- Jeroen Van der Laak, UMC Radboud, Netherlands
- Marius Nap, HistoGeneX, Belgium and Rigshospitalet Copenhagen, Denmark
- Zev Leifer, New York College of Podiatric Medicine, USA
- Yukako Yagi, Harvard Medical School & Massachusetts General Hospital, USA
- Raphaël Marée, Université de Liège, Belgium
Programme
You can now find the preliminary programme here.
Summary
Digital pathology is increasingly used to study biological processes and diseases as novel molecular probing and imaging techniques allow the measurement of single molecules in whole tissue sections. Resulting multi-gigapixel images can be viewed on a computer screen via dedicated software. However, automated analysis of such large-scale datasets is challenging and their combination with omics data is not trivial. This workshop wants to facilitate bridging opportunities between the bioinformatics and tissue image analysis communities.
Examples of topics include:
- Machine learning and image analysis for quantification in digital pathology (in 2D & 3D),
- Novel approaches (e.g. spatial or graph-based methods) to extract high-level features (e.g. molecular networks or spatial expression patterns) from tissue images for systems pathology,
- Software development methodologies and tools to ease the exploitation of large tissue images and integration with omics data,
- Novel molecular imaging techniques on tissues (molecular pathology, next generation pathology) and their analysis challenges, e.g. in situ hybridization, mass spectrometry imaging of formalin-fixed paraffin-embedded tissues, mass cytometry, and other spectroscopy techniques (Raman,…)…
- Research applications on non-human model organisms
Target audience
Bioinformaticians involved with imaging data, histology data, microscopic observations. Researchers that integrate high-resolution data and are looking to correlate this to topographical data.
