通过深度学习预测白内障手术中的术后人工晶状体脱位
Predicting Postoperative Intraocular Lens Dislocation in Cataract Surgery via Deep Learning
AI总结：
本文提出融合循环、区域和像素级 CNN 的全自动框架，从白内障手术视频中量化人工晶状体展开延迟、旋转与稳定性，以预测术后脱位。
摘要：
白内障手术后一个关键但难以预测的并发症是人工晶状体脱位。术后稳定性至关重要，因为即使是多焦点晶状体的微小偏心，或环曲面晶状体因术后旋转导致环曲面部分对齐不充分，都可能造成视力显著下降。研究能够预测人工晶状体术后不稳定性的潜在术中指标，有助于预防这一并发症。本文开发并评估了首个全自动框架，用于计算手术过程中晶状体展开延迟、旋转和不稳定性。所提出的框架结合采用三类 CNN，即循环型、基于区域型和基于像素型 CNN，用于评估在白内障手术期间预测术后晶状体脱位的可能性。为此，本文开展了一项大规模研究，分析不同品牌人工晶状体行为之间的统计学差异，并将结果与专家外科医生关于这些晶状体的假设和观察进行对照。本文利用了一个包含四种人工晶状体品牌的大规模白内障手术视频数据集。实验结果证实了所提出框架在评估手术期间晶状体统计特征方面的可靠性。Pearson 相关性和 t 检验结果揭示了晶状体展开延迟与晶状体旋转之间存在显著相关，并揭示四组晶状体的术中旋转稳定性存在显著差异。这些结果表明，所提出的框架能够帮助外科医生根据患者眼部状况选择晶状体，并预测术后晶状体脱位。
英文摘要：
A critical yet unpredictable complication following cataract surgery is intraocular lens dislocation. Postoperative stability is imperative, as even a tiny decentration of multifocal lenses or inadequate alignment of the torus in toric lenses due to postoperative rotation can lead to a significant drop in visual acuity. Investigating possible intraoperative indicators that can predict post-surgical instabilities of intraocular lenses can help prevent this complication. In this paper, we develop and evaluate the first fully-automatic framework for the computation of lens unfolding delay, rotation, and instability during surgery. Adopting a combination of three types of CNNs, namely recurrent, region-based, and pixel-based, the proposed framework is employed to assess the possibility of predicting post-operative lens dislocation during cataract surgery. This is achieved via performing a large-scale study on the statistical differences between the behavior of different brands of intraocular lenses and aligning the results with expert surgeons' hypotheses and observations about the lenses. We exploit a large-scale dataset of cataract surgery videos featuring four intraocular lens brands. Experimental results confirm the reliability of the proposed framework in evaluating the lens' statistics during the surgery. The Pearson correlation and t-test results reveal significant correlations between lens unfolding delay and lens rotation and significant differences between the intra-operative rotations stability of four groups of lenses. These results suggest that the proposed framework can help surgeons select the lenses based on the patient's eye conditions and predict post-surgical lens dislocation.
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