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Progression Detection of Glaucoma from Polarimetric Images

机译:从偏振图像进行青光眼的进展检测

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摘要

Detecting glaucoma progression is crucial for assessing the effectivity of the treatment. This paper describes three methods for detecting progression related changes in polarimetric images of the retinal nerve fiber layer (NFL), both on a global and on a local scale. Detecting global changes proved not to be feasible due to poor reproducibility of the measurements at the pixel level. Local progression on the other hand could be detected. A distribution based approach did not work, but locating specific areas with minimum size and minimum NFL decrease did give relevant results. The described algorithm yielded a TPR of 0.42 and an FPR of 0.095 on our datasets. It proved to be able to outline suspect areas that show NFL reduction.
机译:检测青光眼的进展对于评估治疗的有效性至关重要。本文介绍了三种检测视网膜神经纤维层(NFL)极化图像中与进展相关的变化的方法,无论是在全局范围内还是在局部范围内。由于在像素级别进行的测量的可重复性差,因此检测全局变化被证明是不可行的。另一方面,可以检测到局部进展。基于分布的方法行不通,但是以最小的尺寸和最小的NFL减少定位特定区域确实可以提供相关的结果。所描述的算法在我们的数据集上产生的TPR为0.42,FPR为0.095。事实证明,它能够勾勒出显示NFL减少的可疑区域。

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