Dr Tristan Whitmarsh
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About
With a Master's degree in Computer Graphics, I made a switch to the field of Medical Image Analysis while working towards a PhD degree, which I was awarded in 2012. After my PhD I joined the Department of Engineering of the University of Cambridge as a postdoctoral researcher in the Medical Imaging Group. I was awarded a University of Cambridge/ Wellcome Trust Junior Interdisciplinary Fellowship at the Department of Medicine in 2015 and a Canon Foundation Fellowship at NAIST in 2016. During an Oxford Biodesign fellowship in the following year, I gained the knowledge and experience to find unmet clinical needs, develop novel biomedical technologies to address these needs, and subsequent take these innovations from the bench to the bedside through various commercial routes. I am the co-inventor and lead developer a point of care medical device for the diagnosis of deep vein thrombosis. I develped and trained convolutional neural networks for the automatic segmentation of the tumor vasculature microenvironment at the Cancer Research UK Cambridge Institute, after which I joined the IMAXT project located at the Institute of Astronomy at the University of Cambridge. In this CRUK Grand Challenge project I continue to use a broad range of image analysis and deep learning techniques to quantify tumor tissue from high resolution 3D fluorescence microscopy images. I also developed ScanXm, a standalone desktop application for the visualization, annotation and segmentation of biomedical images.
ResearchMy interests broadly lie in biomedical image analysis. This includes various modalities such as radiology, pathology, and, more recently, spatial proteomics. I have a particular interest in the field of bone research. I am also interested in medical device development and have developed and patented a device for the diagnosis of deep vein thrombosis, which is currently undergoing a clinical trial. Additionally, I am passionate about entrepreneurship and have founded Minogame to release my biomedical image segmentation tool, ScanXm.