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技术，用于评估视觉通路的病理或功能障碍。VF试验与其他诊断一起用于检测青光眼并跟踪其进展。早期发现至关重要，因为青光眼导致的失明在几乎所有病例中都是可以预防的，只要在进展早期进行治疗。需要一种自动化的决策辅助工具来促进和标准化解释任务。在第一阶段的可行性论证成功之后，第二阶段将应用新的机器学习方法来解决青光眼问题

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.