Camara José, Neto Alexandre, Pires Ivan Miguel, Villasana María Vanessa, Zdravevski Eftim, Cunha António
Departamento de Ciências e Tecnologia, Universidade Aberta, 1250-100 Lisboa, Portugal.
Instituto de Engenharia de Sistemas e Computadores, Tecnologia e Ciência, 3200-465 Porto, Portugal.
Diagnostics (Basel). 2022 Apr 8;12(4):935. doi: 10.3390/diagnostics12040935.
Glaucoma is a chronic optic neuropathy characterized by irreversible damage to the retinal nerve fiber layer (RNFL), resulting in changes in the visual field (VC). Glaucoma screening is performed through a complete ophthalmological examination, using images of the optic papilla obtained in vivo for the evaluation of glaucomatous characteristics, eye pressure, and visual field. Identifying the glaucomatous papilla is quite important, as optical papillary images are considered the gold standard for tracking. Therefore, this article presents a review of the diagnostic methods used to identify the glaucomatous papilla through technology over the last five years. Based on the analyzed works, the current state-of-the-art methods are identified, the current challenges are analyzed, and the shortcomings of these methods are investigated, especially from the point of view of automation and independence in performing these measurements. Finally, the topics for future work and the challenges that need to be solved are proposed.
青光眼是一种慢性视神经病变,其特征是视网膜神经纤维层(RNFL)发生不可逆损伤,进而导致视野(VC)改变。青光眼筛查通过全面的眼科检查进行,利用在体获得的视乳头图像来评估青光眼特征、眼压和视野。识别青光眼性视乳头非常重要,因为视乳头光学图像被视为追踪的金标准。因此,本文综述了过去五年通过技术手段识别青光眼性视乳头的诊断方法。基于所分析的研究成果,确定了当前的先进方法,分析了当前面临的挑战,并研究了这些方法的不足之处,特别是从执行这些测量的自动化和独立性角度。最后,提出了未来工作的主题以及需要解决的挑战。