Muijzer Marc B, Heslinga Friso G, Couwenberg Floor, Noordmans Herke-Jan, Oahalou Abdelkarim, Pluim Josien P W, Veta Mitko, Wisse Robert P L
Utrecht Cornea Research Group, Ophthalmology Department, University Medical Center Utrecht, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands.
Contributed equally.
Biomed Opt Express. 2022 Apr 8;13(5):2683-2694. doi: 10.1364/BOE.446519. eCollection 2022 May 1.
Correct Descemet Membrane Endothelial Keratoplasty (DMEK) graft orientation is imperative for success of DMEK surgery, but intraoperative evaluation can be challenging. We present a method for automatic evaluation of the graft orientation in intraoperative optical coherence tomography (iOCT), exploiting the natural rolling behavior of the graft. The method encompasses a deep learning model for graft segmentation, post-processing to obtain a smooth line representation, and curvature calculations to determine graft orientation. For an independent test set of 100 iOCT-frames, the automatic method correctly identified graft orientation in 78 frames and obtained an area under the receiver operating characteristic curve (AUC) of 0.84. When we replaced the automatic segmentation with the manual masks, the AUC increased to 0.92, corresponding to an accuracy of 86%. In comparison, two corneal specialists correctly identified graft orientation in 90% and 91% of the iOCT-frames.
正确的后弹力层内皮角膜移植术(DMEK)植片方向对于DMEK手术的成功至关重要,但术中评估可能具有挑战性。我们提出了一种在术中光学相干断层扫描(iOCT)中自动评估植片方向的方法,利用植片的自然卷曲行为。该方法包括用于植片分割的深度学习模型、用于获得平滑线表示的后处理以及用于确定植片方向的曲率计算。对于100个iOCT图像帧的独立测试集,该自动方法在78个图像帧中正确识别了植片方向,并且受试者操作特征曲线(AUC)下的面积为0.84。当我们用手动掩码替换自动分割时,AUC增加到0.92,对应于86%的准确率。相比之下,两位角膜专家在90%和91%的iOCT图像帧中正确识别了植片方向。