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Threshold static perimetry is generally done using automated equipment. It is used for rapid screening and follow-up of diseases involving deficits such as scotomas, loss of peripheral vision and more subtle vision loss. Perimetry testing is important in the screening, diagnosing, and monitoring of various eye, retinal, optic nerve and brain ...
The SITA algorithm optimizes the determination of perimetry thresholds by continuously estimating what the expected threshold is based on the patient's age and neighboring thresholds. In this manner, it can reduce the time necessary to acquire a visual field by up to 50%, and it decreases patient fatigue and increases reliability.
A negative value indicates field loss, while a positive value indicates that the field is above average. A P value is provided if the global indices are abnormal. It provides a statistical representation of the population. For example, P <2% means that less than 2% of the population have vision loss worse than measured [19]
The visual field is measured by perimetry.This may be kinetic, where spots of light are shown on the white interior of a half sphere and slowly moved inwards until the observer sees them, or static, where the light spots are flashed at varying intensities at fixed locations in the sphere until detected by the subject.
However, in most fielded systems, unwanted clutter and interference sources mean that the noise level changes both spatially and temporally. In this case, a changing threshold can be used, where the threshold level is raised and lowered to maintain a constant probability of false alarm. This is known as constant false alarm rate (CFAR) detection.
An example of a threshold graph. In graph theory, a threshold graph is a graph that can be constructed from a one-vertex graph by repeated applications of the following two operations: Addition of a single isolated vertex to the graph. Addition of a single dominating vertex to the graph, i.e. a single vertex that is connected to all other vertices.
In image processing, the balanced histogram thresholding method (BHT), [1] is a very simple method used for automatic image thresholding.Like Otsu's Method [2] and the Iterative Selection Thresholding Method, [3] this is a histogram based thresholding method.
The simplest thresholding methods replace each pixel in an image with a black pixel if the image intensity , is less than a fixed value called the threshold , or a white pixel if the pixel intensity is greater than that threshold. In the example image on the right, this results in the dark tree becoming completely black, and the bright snow ...