Leedham & Rittscher Lunchtime Lab & MCTIG Talk


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Speakers will be from the Leedham & Rittscher groups:

Leedham Group
Speaker: Ryan Schenck
Title: Using methylation patterns to understand stem cell dynamics in the crypt and blood

Rittscher Group
This is a MCTIG talk. The Molecular, Cellular and Tissue Imaging Group is a new committee we have set-up in the WHG.
Speaker: Prof Jens Rittscher
Title: AI – New Horizons for Histophathology and Early Cancer Detection

Abstract: Machine learning and image analysis allows to interrogate morphological patterns with a precision and accuracy that exceeds human performance. The talk will highlight recent results that demonstrate the possibility of identifying morphological correlates of molecular subtypes in colorectal cancer using histology alone. Not only will this technology open up new opportunities for cellular pathology, it will also provide new ways for introducing certain molecular tests into the clinical workflow. Combined with new tissue imaging technologies that can visualise multiple different proteins in the same tissue section we can now interrogate tissues with a depth and resolution that has not been possible before. In addition, I outline efforts for improving early detection of oesophageal cancer using computer aided endoscopy.

Bio: Jens Rittscher is Professor of Engineering Science at the University of Oxford with his appointment held jointly between the Institute of Biomedical Engineering and the Nuffield Department of Medicine. He is a group leader at the Big Data Institute and affiliated to the Ludwig Institute of Cancer Research. Previously, he was a senior research scientist and manager at GE Global Research in America. His research interests lie in enabling biomedical imaging through the development of new algorithms and novel computational platforms, with a current focus to improve mechanistic understanding of cancer and patient care through quantitative analysis of image data. He is a co-director of the Oxford EPSRC Centre for Doctoral Training in Health Data Science.