Diagnostic aid software for the visual field test

视野（VF）测试是一种广泛使用的，非侵入性的技术，用于评估病理或功能障碍的视觉路径。VF测试，结合其他诊断，用于检测青光眼和跟踪其进展。早期发现是至关重要的，因为青光眼致盲在几乎所有情况下都是可以预防的，只要在进展的早期给予治疗。需要一种自动化的辅助决策工具，以便利口译工作并使之标准化。在第一阶段成功的可行性论证之后，第二阶段将应用新的机器学习方法来解决青光眼问题 通过视野和辅助数据的自动分析进行诊断。IAC将开发一个集成的、用户友好的软件程序，该软件程序将提供昏迷性和非昏迷性缺陷的可靠详细分类，重点是昏迷性缺陷和早期检测。其目的是实现接近于高度熟练的人类专家的分类精度。由软件建议的诊断将得到一组从分类算法中提取的综合规则的支持。可选地，该程序将提供视野和青光眼进展的测量。

Visual field (VF) test is a widely used, noninvasive technique for evaluating pathology or dysfunction in the visual pathways. The VF test, in conjunction with other diagnostics, is used for detection of laucoma and for following its progression. Early detection is critical as blindness from glaucoma is preventable in nearly all cases, provided treatment is administered early in the progression. There is a need for an automated decision aid tool that will facilitate and standardize the interpretation task. Following a successful Phase I feasibility demonstration, Phase II will apply novel machine learning approaches to the problem of glaucoma diagnosis via an automated analysis of visual field and ancillary data. IAC will develop an integrated, user friendly software program that will provide a reliable detailed classification of glaucomatous and non-glaucomatous defects with the main emphasis on glaucomatous defects and early detection. The aim is to achieve classification accuracy close to that of a highly skilled human expert. The diagnosis suggested by the software will be supported by a set of comprehensive rules extracted from the classification algorithm. Optionally, the program will provide measures of visual field and glaucoma progression.