AI 中文总结
本研究针对近视眼底图像中OD/PPA分割碎片化及量化依赖后处理的问题，提出UPolarSQ极坐标域框架，经实验验证可提升分割性能并实现可靠的生物标志物估计。
AI 中文摘要
近视诱发的后极部重塑常伴随视盘（Optic Disc, OD）变形及视盘周围萎缩（Peripapillary Atrophy, PPA），二者均为具有临床相关性的结构生物标志物。然而在笛卡尔坐标系的眼底图像中，PPA常表现为视盘旁不规则且部分可见的新月形，导致分割结果碎片化及依赖后处理的量化。本文提出UPolarSQ，一种用于近视眼底图像中OD/PPA分割及生物标志物量化的统一极坐标域框架。UPolarSQ首先将以OD为中心的感兴趣区域映射至极坐标，使OD与PPA边界可表示为径向轮廓；随后采用UPolarSeg——一种基于U-Net的分割网络，该网络经径向-角向解耦模块及边界感知辅助监督增强，以建模各向异性极坐标特征与径向边界过渡。从预测的极坐标掩码中确定性提取包括视盘形状、PPA宽度相关测量在内的临床生物标志物，在共享几何表示内实现分割与量化的统一。在内部及外部队列上的实验表明，UPolarSQ可提升OD/PPA分割性能，并支持用于近视分析的可靠极坐标原生生物标志物估计。
英文摘要
Myopia-induced posterior-pole remodeling is frequently accompanied by Optic Disc (OD) deformation and Peripapillary Atrophy (PPA), both of which provide clinically relevant structural biomarkers. In Cartesian fundus images, however, PPA often appears as an irregular and partially visible crescent adjacent to the OD, leading to fragmented segmentation and post-processing-dependent quantification. We propose UPolarSQ, a unified polar-domain framework for OD/PPA segmentation and biomarker quantification in myopic fundus images. UPolarSQ first maps an OD-centered region of interest into polar coordinates, where OD and PPA boundaries can be represented as radial profiles. It then employs UPolarSeg, a U-Net-based segmentation network enhanced with a Radial-Angular-Decoupled Module and boundary-aware auxiliary supervision to model anisotropic polar features and radial boundary transitions. Clinical biomarkers, including disc shape and PPA-width-related measurements, are deterministically extracted from the predicted polar masks, aligning segmentation and quantification within a shared geometric representation. Experiments on internal and external cohorts demonstrate that UPolarSQ improves OD/PPA segmentation and supports reliable polar-native biomarker estimation for myopic analysis.
