Perception Engineering, Eberhard-Karls-University Tübingen, Sand 14, 72076 Tübingen, Germany.
Institute of Technical Optics, University Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany.
Comput Biol Med. 2016 Dec 1;79:36-44. doi: 10.1016/j.compbiomed.2016.10.005. Epub 2016 Oct 7.
Modern microsurgery is a long and complex task requiring the surgeon to handle multiple microscope controls while performing the surgery. Eye tracking provides an additional means of interaction for the surgeon that could be used to alleviate this situation, diminishing surgeon fatigue and surgery time, thus decreasing risks of infection and human error. In this paper, we introduce a novel algorithm for pupil detection tailored for eye images acquired through an unmodified microscope ocular. The proposed approach, the Hough transform, and six state-of-the-art pupil detection algorithms were evaluated on over 4000 hand-labeled images acquired from a digital operating microscope with a non-intrusive monitoring system for the surgeon eyes integrated. Our results show that the proposed method reaches detection rates up to 71% for an error of ≈3% w.r.t the input image diagonal; none of the state-of-the-art pupil detection algorithms performed satisfactorily. The algorithm and hand-labeled data set can be downloaded at:: www.ti.uni-tuebingen.de/perception.
现代微创手术是一项漫长而复杂的任务，要求外科医生在进行手术的同时处理多个显微镜控制。眼动追踪为外科医生提供了一种额外的交互手段，可以用来缓解这种情况，减少外科医生的疲劳和手术时间，从而降低感染和人为错误的风险。在本文中，我们介绍了一种针对通过未经修改的显微镜目镜采集的眼图像量身定制的瞳孔检测新算法。所提出的方法，即霍夫变换，以及六种最先进的瞳孔检测算法，在超过 4000 张由集成了用于监视外科医生眼睛的非侵入性监测系统的数字手术显微镜采集的手标记图像上进行了评估。我们的结果表明，对于相对于输入图像对角线的 ≈3%的误差，所提出的方法的检测率高达 71%；没有一种最先进的瞳孔检测算法表现令人满意。该算法和手标记数据集可在以下网址下载：::www.ti.uni-tuebingen.de/perception。
