A free-hand scanning approach to medical imaging allows for flexible, lightweight probes to image intricate anatomies for modalities such as fluorescence lifetime imaging (FLIm), optical coherence tomography (OCT) and ultrasound. While very promising, this approach faces several key challenges including tissue motion during imaging, varying lighting conditions in the surgical field, and sparse sampling of the tissue surface. These challenges limit the coregistration accuracy and interpretability of the acquired imaging data. Here we report FLImBrush as a robust method for the localization and visualization of intraoperative free-hand fiber optic fluorescence lifetime imaging (FLIm). FLImBrush builds upon an existing method while employing deep learning-based image segmentation, block-matching based motion correction, and interpolation-based visualization to address the aforementioned challenges. Current results demonstrate that FLImBrush can provide accurate localization of FLIm point-measurements while producing interpretable and complete visualizations of FLIm data acquired from a tissue surface. Each of the main processing steps was shown to be capable of real-time processing (> 30 frames per second), highlighting the feasibility of FLImBrush for intraoperative imaging and surgical guidance. Current findings show the feasibility of integrating FLImBrush into a range of surgical applications including cancer margins assessment during head and neck surgery.

中文翻译：

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FLImBrush：术中基于手部纤维的荧光寿命成像的动态可视化

一种用于医学成像的徒手扫描方法，允许灵活，轻巧的探头对复杂的解剖结构进行成像，以用于诸如荧光寿命成像（FLIm），光学相干断层扫描（OCT）和超声检查之类的方式。尽管非常有前途，但是这种方法面临几个关键挑战，包括成像过程中的组织运动，手术区域中变化的光照条件以及组织表面的稀疏采样。这些挑战限制了获取的成像数据的配准精度和可解释性。在这里，我们报告FLImBrush作为术中徒手光纤荧光寿命成像（FLIm）的定位和可视化的可靠方法。FLImBrush建立在现有方法的基础上，同时采用了基于深度学习的图像分割，基于块匹配的运动校正，基于插值的可视化解决了上述挑战。当前结果表明，FLImBrush可以提供FLIm点测量的准确定位，同时可以生成从组织表面获取的FLIm数据的可解释且完整的可视化。每个主要处理步骤均显示为能够实时处理（> 30帧/秒），突显了FLImBrush在术中成像和手术指导中的可行性。目前的发现表明，将FLImBrush集成到一系列外科手术应用中的可行性，包括在头颈外科手术期间进行癌症边缘评估。当前结果表明，FLImBrush可以提供FLIm点测量的精确定位，同时可以产生从组织表面获取的FLIm数据的可解释性和完整可视化。每个主要处理步骤均显示为能够实时处理（> 30帧/秒），突显了FLImBrush在术中成像和手术指导中的可行性。当前的发现表明将FLImBrush集成到一系列外科应用中的可行性，包括在头颈外科手术期间的癌症边缘评估。当前结果表明，FLImBrush可以提供FLIm点测量的精确定位，同时可以产生从组织表面获取的FLIm数据的可解释性和完整可视化。每个主要处理步骤均显示为能够实时处理（> 30帧/秒），突显了FLImBrush在术中成像和手术指导中的可行性。当前的发现表明将FLImBrush集成到一系列外科应用中的可行性，包括在头颈外科手术期间的癌症边缘评估。