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Fine-Scale Vessel Extraction in Fundus Images by Registration with Fluorescein Angiography

机译:通过荧光素血管造影术对眼底图像进行精细血管提取

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We present a new framework for fine-scale vessel segmentation from fundus images through registration and segmentation of corresponding fluorescein angiography (FA) images. In FA, fluorescent dye is used to highlight the vessels and increase their contrast. Since these highlights are temporally dispersed among multiple FA frames, we first register the FA frames and aggregate the per-frame segmentations to construct a detailed vessel mask. The constructed FA vessel mask is then registered to the fundus image based on an initial fundus vessel mask. Postprocessing is performed to refine the final vessel mask. Registration of FA frames, as well as registration of FA vessel mask to the fundus image, are done by similar hierarchical coarse-to-fine frameworks, both comprising rigid and non-rigid registration. Two CNNs with identical network structures, both trained on public datasets but with different settings, are used for vessel segmentation. The resulting final vessel segmentation contains fine-scale, filamentary vessels extracted from FA and corresponding to the fundus image. We provide quantitative evaluation as well as qualitative examples which support the robustness and the accuracy of the proposed method.
机译:我们提出了一种新的框架,可以通过对相应的荧光素血管造影(FA)图像进行配准和分割,从眼底图像中进行精细的血管分割。在FA中,荧光染料用于突出显示血管并增加其对比度。由于这些亮点在时间上分散在多个FA帧中,因此我们首先注册FA帧并汇总每帧分割以构造详细的血管蒙版。然后基于初始的眼底血管面罩将构造的FA血管面罩配准至眼底图像。执行后处理以完善最终的容器蒙版。 FA框架的配准以及FA血管罩到眼底图像的配准均通过类似的从粗到细的分层框架完成,包括刚性和非刚性配准。具有相同网络结构的两个CNN(均在公共数据集上训练但设置不同)用于血管分割。最终的血管分割包含从FA中提取的对应于眼底图像的细鳞状丝状血管。我们提供定量评估以及定性实例,以支持所提出方法的鲁棒性和准确性。

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