Real-time software improves eye nerve imaging for health checks
CRISP: Corneal Confocal Microscopy Real-Time Image Stitching Pipeline
Computer Vision and Pattern Recognition
Summary
Checking the health of tiny nerves in the eye can help doctors understand nerve-related diseases, but current microscope images only capture small spots, making it hard to get the full picture. The authors created software called CRISP that can stitch together multiple small microscope images of the eye's nerve layers quickly and automatically while the images are being taken. This real-time approach helps ensure clear, wide views without needing extra equipment or special routines. Their tool is freely available, which could make detailed eye nerve imaging easier to use in everyday medical exams.
Corneal confocal microscopySub-basal nerve plexusReal-time image stitchingPeripheral nerve healthWide-field imagingImage registrationVideo stream processingOpen-source softwareFocus-aware gatingClinical imaging workflow
Authors
Qincheng Qiao, Puli Zhang, Jian Zhou, Xinguo Hou
Abstract
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.