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  1. No Access

    Chapter and Conference Paper

    Unsupervised 3D Brain Anomaly Detection

    Anomaly detection (AD) is the identification of data samples that do not fit a learned data distribution. As such, AD systems can help physicians to determine the presence, severity, and extension of a patholo...

    Jaime Simarro Viana, Ezequiel de la Rosa… in Brainlesion: Glioma, Multiple Sclerosis, S… (2021)

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    Chapter and Conference Paper

    Improved Inter-scanner MS Lesion Segmentation by Adversarial Training on Longitudinal Data

    The evaluation of white matter lesion progression is an important biomarker in the follow-up of MS patients and plays a crucial role when deciding the course of treatment. Current automated lesion segmentation...

    Mattias Billast, Maria Ines Meyer… in Brainlesion: Glioma, Multiple Sclerosis, S… (2020)

  3. No Access

    Chapter and Conference Paper

    Unsupervised Framework for Consistent Longitudinal MS Lesion Segmentation

    Quantification of white matter lesion changes on brain magnetic resonance (MR) images is of major importance for the follow-up of patients with Multiple Sclerosis (MS). Many automated segmentation methods have...

    Saurabh Jain, Annemie Ribbens, Diana M. Sima… in Medical Computer Vision and Bayesian and G… (2017)