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@Sentinal4D

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DeVriesMatt/README.md

Hello! 👋

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My website

I am a PhD student at the Insitute of Cancer Research and Imperial College London researching Deep Learning in Cancer Biology under the supervision of Chris Bakal and Chris Dunsby. My PhD is part of the CRUK Accelerator award. I have an undergraduate degree in Statistics from the University of Cape Town and a master's degree in Artificial Intelligence from the University of Southampton.

My current work focuses on developing computer vision techniques to understand live 3D cancer biology. My research interests are in Geometric Deep Learning, 3D Computer Vision, Shape Analysis and Explainable AI.

Please see my organisations - Sentinal4D and MagniViT - for my work on geometric deep learning in cancer biology, and vision transformers for classification of soft tissue sarcoma from whole slide images.

Aside from my work and research, I am an avid runner, swimmer, cyclist, and footballer.

Statistics about my profile (Click to expand!)

Github Stats By DeVriesMatt Github Langs By DeVriesMatt

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  1. Sentinal4D/cellshape Sentinal4D/cellshape Public

    3D shape analysis using deep learning

    Python 21 6

  2. Sentinal4D/cellshape-cloud Sentinal4D/cellshape-cloud Public

    Jupyter Notebook 5 3

  3. Sentinal4D/cellshape-voxel Sentinal4D/cellshape-voxel Public

    Cellshape-voxel is an easy-to-use tool to analyse the shapes of cells using deep learning and, in particular, 3D convolutional neural networks.

    Python 5

  4. Sentinal4D/cellshape-cluster Sentinal4D/cellshape-cluster Public

    Cellshape-cluster is an easy-to-use tool to analyse the cluster cells by their shape using deep learning and, in particular, deep-embedded-clustering

    Python 4 1

  5. Sentinal4D/cellshape-helper Sentinal4D/cellshape-helper Public

    Cellshape-helper provides the ability to convert 3D masks to point clouds.

    Python 2 3

  6. 3D-denoising-diffusion-pytorch 3D-denoising-diffusion-pytorch Public

    Forked from lucidrains/denoising-diffusion-pytorch

    Implementation of Denoising Diffusion Probabilistic Model in Pytorch

    Jupyter Notebook