眼科人工智能的算法新进展

New developments in ophthalmic AI algorithms

随着高效的深度神经网络算法、大量高质量医学数据、低成本大规模计算机并行设备的普及,近年来人工智能在眼科领域、院内眼科疾病筛查和院外体检中心都取得了大规模的应用。对某些特定疾病如眼底糖网已经达到甚至超过了大多数全科大夫的水准。在本文中我们以分类、检测、分割、域适应等基础算法为引子,梳理、分析出人工智能在眼科应用中的优势和不足,以便更好地构想未来的研究方向。

Deep neural networks,combined with high quality annotated medical data and low-cost GPU devices,have been successfully implemented in the field of ophthalmology.Impressive grounding outcomes have occurred in both in-hospital and out-hospital scenarios.Some of the published results demonstrated AI could achieve better diagnosis performance than general practice in the diagnosis of certain retinal diseases.In this article,we will discuss how classification,detection,segmentation and domain adaptation play their roles in AI ophthalmology.We will also discuss the limitations of the current state-of-the-art(SOTA)algorithms,hoping to provide prevision for future research in this field.