自动化感知驱动评估配对临床照片摄影一致性：流程开发与内部评估
Automated Perceptually-Motivated Assessment of Photographic Consistency in Paired Clinical Photographs: Pipeline Development and Internal Evaluation
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- David Geffen School of Medicine at UCLA（加州大学洛杉矶分校大卫·格芬医学院）
- Cornell University（康奈尔大学）
- Tulane University（杜兰大学）
- University of Pittsburgh School of Medicine（匹兹堡大学医学院）
机构由 AI 辅助整理，请以论文原文为准。
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中文总结 AI 辅助
本研究开发了一个感知驱动的自动化流程，通过十三个校准子指标和五个数据驱动聚类，生成单一一致性评分S，以客观评估配对临床照片的可比性，区分匹配与不匹配配对，并提供免费网络工具用于审计。
中文摘要 AI 辅助
目的：配对术前和术后照片是整形外科结果的标准证据单位，然而尚无客观指标验证同一患者的两张图像是否在可比较的条件下拍摄。方法：我们开发了一个感知驱动的流程，该流程通过十三个校准的子指标分析术前/术后配对，通过无监督相关结构分析将其划分为五个数据驱动的聚类（光度、纹理/清晰度、姿态、光照方向和俯仰角），在每个聚类内取平均值，并通过加权和跨聚类组合成单一的一致性评分。每个子指标经过校准，使得已发表的患者内配对的中位差异评分为0.5，这是一个参考点，不具有通过/失败含义。该流程在134对匹配的已发表患者内术前/术后配对上进行了校准，并针对相同图像对、合成扰动对和134对不匹配的跨出版物配对进行了评估。结果：主一致性评分S区分了匹配和不匹配的配对（灵敏度指数d' = 2.15，95%置信区间[1.83, 2.55]；接收者操作特征曲线下面积AUC = 0.928，95%置信区间[0.896, 0.959]），与高斯等方差预测密切匹配。三个头部姿态角度未落入同一聚类：偏航角和滚转角归为一组，而俯仰角分离。相同配对得分达到上限（S = 0.99），主评分在所有五个扰动轴上随扰动幅度单调下降。结论：该评分量化了照片可比性，而非美学或手术质量，并提供了一个免费可用的网络工具，用于审计术前/术后配对的照片可比性，有待专家判断验证。
英文摘要
Purpose: Paired pre- and post-operative photographs are the standard unit of evidence for plastic surgical outcomes, yet no objective metric verifies whether two images of the same patient were captured under conditions consistent for comparison. Approach: We developed a perceptually motivated pipeline that analyzes pre/post pairs across thirteen calibrated sub-metrics, partitioned by unsupervised correlation-structure analysis into five data-driven clusters (photometric, texture / sharpness, pose, illumination direction, and pitch), averaged within each cluster and combined across clusters by a weighted sum into a single consistency score. Each sub-metric is calibrated so that its median difference across published within-patient pairs scores 0.5, which is a reference point and carries no pass/fail meaning. The pipeline was calibrated on 134 matched within-patient published pre/post pairs and evaluated against identical-image pairs, synthetic-perturbation pairs, and 134 mismatched cross-publication pairs. Results: The master consistency score S separated matched from mismatched pairs (sensitivity index d' = 2.15, 95% confidence interval (CI) [1.83, 2.55]; area under the receiver operating characteristic curve AUC = 0.928, 95% CI [0.896, 0.959]), closely matching Gaussian-equal-variance predictions. The three head-pose angles did not fall in one cluster: yaw and roll grouped together while pitch separated. Identical pairs scored at ceiling (S = 0.99) and the master score fell monotonically with perturbation magnitude on all five perturbation axes. Conclusions: The score quantifies photographic comparability, not aesthetic or surgical quality, and provides a freely available web tool for auditing the photographic comparability of pre/post pairs, pending validation against expert judgment.
