Thermographic imaging accompanied with time-resolved analysis is a promising technique for intraoperative imaging in neurosurgery. However, motion due to breathing and pulse of the patient introduces large inaccuracies to the demarcation of normal and pathological brain tissue. Since movements and physiological processes are both manifested as temperature variations, we employ co-registered visual-light images to unambiguously detect motion. In this article, we propose a feature-based approach which is selected from four best-known methods after thorough performance comparison. Complementing our previous work, we evaluate the performance of our methods by applying a frequency analysis and similarity measurements. Our approach enables an accurate motion correction without affecting physiological temperature shifts. Furthermore, real-time performance of the implementation is enabled by serial acceleration and parallelization methods.

中文翻译：

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多模式术中成像中的运动校正。

热成像与时间分辨分析相结合是神经外科术中成像的一种有前途的技术。但是，由于患者的呼吸和脉搏引起的运动会给正常和病理性脑组织的界线带来很大的误差。由于运动和生理过程均表现为温度变化，因此我们采用共同注册的可见光图像来明确检测运动。在本文中，我们提出了一种基于功能的方法，经过全面的性能比较后，该方法是从四种最著名的方法中选择的。作为对先前工作的补充，我们通过应用频率分析和相似性评估来评估方法的性能。我们的方法可以在不影响生理温度变化的情况下进行准确的运动校正。此外，