Percutaneous image-guided interventions are commonly used for the diagnosis and treatment of cancer. In practice, physiological breathing-induced motion increases the difficulty of accurately inserting needles into tumors without impairing the surrounding vital structures. In this work, we propose a data-driven patient-specific hierarchical respiratory motion estimation framework to accurately estimate the position of a tumor and surrounding vital tissues in real time.

中文翻译：

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用于图像引导干预的胸腹器官的微分形呼吸运动估计

经皮图像引导干预通常用于癌症的诊断和治疗。在实践中，生理呼吸引起的运动增加了将针准确插入肿瘤而不损害周围重要结构的难度。在这项工作中，我们提出了一个数据驱动的特定于患者的分层呼吸运动估计框架，以实时准确地估计肿瘤和周围重要组织的位置。