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  1. No Access

    Chapter and Conference Paper

    Consistency-Based Semi-supervised Evidential Active Learning for Diagnostic Radiograph Classification

    Deep learning approaches achieve state-of-the-art performance for classifying radiology images, but rely on large labelled datasets that require resource-intensive annotation by specialists. Both semi-supervis...

    Shafa Balaram, Cuong M. Nguyen… in Medical Image Computing and Computer Assis… (2022)

  2. No Access

    Chapter and Conference Paper

    Semi-supervised Classification of Diagnostic Radiographs with NoTeacher: A Teacher that is Not Mean

    Deep learning approaches offer strong performance for radiology image classification, but are bottlenecked by the need for large labeled training datasets. Semi-supervised learning (SSL) methods that can lever...

    Balagopal Unnikrishnan, Cuong Manh Nguyen… in Medical Image Computing and Computer Assis… (2020)

  3. No Access

    Chapter and Conference Paper

    A Maximum Entropy Deep Reinforcement Learning Neural Tracker

    Tracking of anatomical structures has multiple applications in the field of biomedical imaging, including screening, diagnosing and monitoring the evolution of pathologies. Semi-automated tracking of elongated...

    Shafa Balaram, Kai Arulkumaran, Tianhong Dai… in Machine Learning in Medical Imaging (2019)