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3 Result(s)

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  1. No Access

    Chapter and Conference Paper

    Hierarchical Compositionality in Hyperbolic Space for Robust Medical Image Segmentation

    Deep learning based medical image segmentation models need to be robust to domain shifts and image distortion for the safe translation of these models into clinical practice. The most popular methods for impro...

    Ainkaran Santhirasekaram, Mathias Winkler… in Domain Adaptation and Representation Trans… (2024)

  2. No Access

    Chapter and Conference Paper

    A Sheaf Theoretic Perspective for Robust Prostate Segmentation

    Deep learning based methods have become the most popular approach for prostate segmentation in MRI. However, domain variations due to the complex acquisition process result in textural differences as well as i...

    Ainkaran Santhirasekaram, Karen Pinto… in Medical Image Computing and Computer Assis… (2023)

  3. No Access

    Chapter and Conference Paper

    Multi-scale Hybrid Transformer Networks: Application to Prostate Disease Classification

    Automated disease classification could significantly improve the accuracy of prostate cancer diagnosis on MRI, which is a difficult task even for trained experts. Convolutional neural networks (CNNs) have show...

    Ainkaran Santhirasekaram, Karen Pinto… in Multimodal Learning for Clinical Decision … (2021)