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通过遮盖试验对数字视频中的斜视进行自动诊断。

Automatic diagnosis of strabismus in digital videos through cover test.

作者信息

Valente Thales Levi Azevedo, de Almeida João Dallyson Sousa, Silva Aristófanes Corrêa, Teixeira Jorge Antonio Meireles, Gattass Marcelo

机构信息

Federal University of Maranhão - UFMA, Applied Computing Group - NCA/UFMA, Av. dos Portugueses, SN, Campus do Bacanga, Bacanga 65085-580, São Luís, MA, Brazil.

Pontifical Catholic University of Rio de Janeiro - PUC-Rio, R. São Vicente, 225, Gávea, 22453-900, Rio de Janeiro, RJ, Brazil.

出版信息

Comput Methods Programs Biomed. 2017 Mar;140:295-305. doi: 10.1016/j.cmpb.2017.01.002. Epub 2017 Jan 5.

Abstract

BACKGROUND AND OBJECTIVE

Medical image processing can contribute to the detection and diagnosis of human body anomalies, and it represents an important tool to assist in minimizing the degree of uncertainty of any diagnosis, while providing specialists with an additional source of diagnostic information. Strabismus is an anomaly that affects approximately 4% of the population. Strabismus modifies vision such that the eyes do not properly align, influencing binocular vision and depth perception. Additionally, it results in aesthetic problems, which can be reversed at any age. However, the use of low cost computational resources to assist in the diagnosis and treatment of strabismus is not yet widely available. This work presents a computational methodology to automatically diagnose strabismus through digital videos featuring a cover test using only a workstation computer to process these videos.

METHODS

The method proposed was validated in patients with exotropia and consists of eight steps: (1) acquisition, (2) detection of the region surrounding the eyes, (3) identification of the location of the pupil, (4) identification of the location of the limbus, (5) eye movement tracking, (6) detection of the occluder, (7) identification of evidence of the presence of strabismus, and (8) diagnosis.

RESULTS

To detect the presence of strabismus, the proposed method achieved a specificity value of 100%, and (2) a sensitivity value of 80%, with 93.33% accuracy in diagnosis of patients with extropia. This procedure was recognized to diagnose strabismus with an accuracy value of 87%, while acknowledging measures lower than 1Δ, and an average error in the deviation measure of 2.57Δ.

CONCLUSIONS

We demonstrated the feasibility of using computational resources based on image processing techniques to achieve success in diagnosing strabismus by using the cover test. Despite the promising results the proposed method must be validated in a greater volume of video including other types of strabismus.

摘要

背景与目的

医学图像处理有助于人体异常的检测与诊断,是协助降低任何诊断不确定性程度的重要工具,同时为专家提供额外的诊断信息来源。斜视是一种影响约4%人口的异常情况。斜视会改变视力,导致双眼无法正常对齐,影响双眼视觉和深度感知。此外,它还会引发美学问题,且这种问题在任何年龄都可得到纠正。然而,利用低成本计算资源辅助斜视诊断和治疗的方法尚未广泛应用。本文提出一种计算方法,可通过仅使用工作站计算机处理包含遮盖试验的数字视频来自动诊断斜视。

方法

所提出的方法在患有外斜视的患者中进行了验证,包括八个步骤:(1)采集,(2)检测眼睛周围区域,(3)确定瞳孔位置,(4)确定角膜缘位置,(5)眼睛运动跟踪,(6)检测遮挡物,(7)识别斜视存在的证据,(8)诊断。

结果

为检测斜视的存在,所提出的方法特异性值达到100%,灵敏度值为80%,对外斜视患者的诊断准确率为93.33%。该程序被认为诊断斜视的准确率为87%,同时认可低于1Δ的测量值,偏差测量的平均误差为2.57Δ。

结论

我们证明了利用基于图像处理技术的计算资源通过遮盖试验成功诊断斜视的可行性。尽管结果令人鼓舞,但所提出的方法必须在包括其他类型斜视的更多视频中进行验证。

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