发表机构
Qilu Hospital, Shandong University（山东大学齐鲁医院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
CRISP提出首个开源实时角膜神经宽场拼接框架，通过焦点门控、位姿传播和稀疏锚点图实现常规CCM视频流的低延迟拼接，降低临床采用门槛。
AI 中文摘要
角膜上皮下神经丛（SNP）的形态反映周围神经健康状况，角膜共聚焦显微镜（CCM）为体内、实时、无创观察SNP提供了重要手段。然而，主流CCM设备每帧视野有限，而SNP在空间上不均匀；因此离散图像采样对采样位置和帧选择敏感，这限制了CCM作为定量评估工具的可重复性和临床采用。宽场拼接可通过整合顺序采集的CCM图像重建更大的SNP马赛克，但现有方法主要依赖离线后处理、额外硬件或特定采集协议，且缺乏针对常规CCM视频流的开源实时解决方案。本文提出CRISP（角膜共聚焦显微镜实时图像拼接流水线），一个面向常规CCM检查视频流的开源实时SNP宽场拼接框架。CRISP通过焦点感知门控排除离焦和不连续片段，通过局部成对配准传播位姿，并利用稀疏锚点图维持无冗余的空间覆盖；当局部时间连续性中断时，系统通过全局外观检索后进行几何验证来完成重定位和子图合并。该框架在检查期间优先提供低延迟覆盖反馈，同时输出已接受帧、位姿和锚点信息以初始化离线精细拼接。据我们所知，CRISP是首个针对常规CCM视频流发布的开源实时SNP宽场拼接框架。通过降低宽场拼接的采用和复现门槛，CRISP可能有助于将SNP宽场成像从研究工具转变为常规临床检查工作流程。
英文摘要
Morphology of the sub-basal nerve plexus (SNP) reflects peripheral nerve health, and corneal confocal microscopy (CCM) provides an important means for in vivo, real-time, non-invasive observation of the SNP. However, mainstream CCM devices offer a limited field of view per frame, whereas the SNP is spatially non-uniform; discrete image sampling is therefore sensitive to sampling location and frame selection, which limits the reproducibility and clinical adoption of CCM as a quantitative assessment tool. Wide-field stitching can reconstruct larger SNP mosaics by integrating sequentially acquired CCM images, but existing methods largely rely on offline post-processing, additional hardware, or specific acquisition protocols, and lack open-source real-time solutions for conventional CCM video streams. This paper presents CRISP (Corneal confocal microscopy Real-time Image Stitching Pipeline), an open-source real-time SNP wide-field stitching framework for conventional CCM examination video streams. CRISP excludes defocused and discontinuous segments via focus-aware gating, propagates poses through local pairwise registration, and maintains non-redundant spatial coverage with a sparse anchor map; when local temporal continuity is interrupted, the system completes relocalization and subgraph merging through global appearance retrieval followed by geometric verification. The framework prioritizes low-latency coverage feedback during examination while outputting accepted frames, poses, and anchor information to initialize offline fine stitching. To our knowledge, CRISP is the first open-source real-time SNP wide-field stitching framework released for conventional CCM video streams. By lowering the barrier to adoption and reproduction of wide-field stitching, CRISP may help move SNP wide-field imaging from a research tool into routine clinical examination workflows.
Comments7 pages, 2 figures. Code: https://github.com/SummerColdWind/CRISP
