Using PDE-constrained optimization we introduce a parameter identification approach which can identify the blood perfusion rate from MR thermometry data obtained during the treatment with laser-induced thermotherapy (LITT). The blood perfusion rate, i.e., the cooling effect induced by blood vessels, can be identified during the first stage of the treatment. This information can then be used by a simulation to monitor and predict the ongoing treatment. The approach is tested with synthetic measurements with and without artificial noise as input data.

中文翻译：

---

激光诱导肝脏热疗法的血液灌注率鉴定

使用受PDE约束的优化，我们引入了一种参数识别方法，该方法可以从在激光诱导热疗（LITT）治疗期间获得的MR测温数据中识别出血液灌注率。可以在治疗的第一阶段确定血液灌注率，即由血管引起的降温作用。然后，模拟可使用此信息来监视和预测正在进行的治疗。该方法在有或没有人工噪声作为输入数据的情况下进行了综合测量。