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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...
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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...
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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...