University of Cambridge > > Institute of Astronomy Seminars > Quantifying the tumor vasculature environment using deep learning

Quantifying the tumor vasculature environment using deep learning

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The tumor vascular density assessed from CD-31 immunohistochemistry (IHC) images has previously been shown to have prognostic value in breast cancer. Current methods to measure the vascular density, however, are time-consuming, suffer from a high inter-observer variability and are limited in describing the complex tumor vasculature morphometry. We therefore propose a method for automatically measuring a range of vascular parameters from CD-31 IHC images, which together provide a detailed description of the vasculature morphology.

This talk is part of the Institute of Astronomy Seminars series.

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