Abstract
The utilization of deep reinforcement learning (DRL) has brought about a significant transformation in the realm of medical image analysis. By merging the capabilities of deep neural networks with reinforcement learning techniques, DRL has become a potent tool for addressing complex healthcare issues. In this comprehensive survey paper, we delve into the latest developments and approaches in employing DRL for medical image analysis. We thoroughly investigate the primary challenges, methodologies, existing datasets, and offer a glimpse into the future potential of this interdisciplinary field. This exploration underscores the distinctive synergy between DRL and the analysis of medical images.
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