Infrared (IR) spectroscopic imaging and digital pathology for development of algorithm for early detection of test-article related lung findings in th

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Research questionsCan we apply deep learning (AI) to train an algorithm to recognize areas of abnormality in treated and control rat lung tissue infrared spectroscopic images?Can we develop a standardized algorithm that can be applied to infrared spectroscopic images taken from any control and treated rat tissue to enable recognition of adverse findings before histopathology lesions are apparent.Can we use the data from the infrared spectroscopic images and the algorithm trained to recognize adverse respiratory findings in lungs taken from rats on 24 hour inhalation studies. Will the earlier detection of adverse findings in treated lung tissue using the developed algorithm enable Syngenta to conduct fewer animal studies or terminate unsuccessful studies at an earlier stage?This project will continue work from a previous PhD project to develop an algorithm for the detection of adverse findings within control and treated lung tissue taken from recent 28 day inhalation studies with agrochemicals, in rats/mice. While the tissue makeup and constituents will differ, the analytical and modelling techniques developed in the mouse liver study are easily transferrable to lung and the sample preparation and data collection protocols remain unchanged. If these techniques can be proven to be effective across different tissue groups and lesion types, it could lead to the development of a standardised chemical lesion detection algorithm to be implemented in future pathology workflows. This is largely a computational and AI project which aims to build on work from a previous PhD student. This project will explore new methods and new network architectures that will enable us to extract the maximum amount of information from each sample. The novel science will be in the algorithm development. This is within the EPSRC remit and it is expected that the student will have a computational science / AI background