Investigative ophthalmology & visual science · 2011
Quantification of parapapillary atrophy and optic disc.
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Lu Cheng-Kai, Tang Tong Boon, Laude Augustinus, Deary Ian J, Dhillon Baljean, Murray Alan F
Аннотация
PURPOSE: A computer-aided measuring tool was devised to automatically detect and quantify both the parapapillary atrophy (PPA) and the optic disc (OD) regions in two-dimensional color fundus images of the retina.
METHODS: The OD region was segmented using the Chan-Vese model with a shape restraint. This region was then removed from the image (OD+PPA), which was cropped in a modified Chan-Vese approach, producing a first-order estimation of the PPA region. Its boundary is subsequently refined by using thresholding, a scanning filter, and multiseed region-growing methods. Dual channels (blue and red) in the red-green-blue space are used to minimize the interference effects of blood vessels and artifacts.
RESULTS: The software was tested on 94 randomly selected images of eyes with PPA from 66 subjects of a well-characterized cohort database. Our proposed algorithm achieved a mean accuracy level of 93.8% (SD 5.26) and 94.0% (SD 5.88) in estimating the size of the PPA and OD respectively, compared with the ground estimate defined by an ophthalmologist. In terms of correlation between the data of the ground estimate and our estimation, we obtained a correlation coefficient of 0.98 for both the PPA and the OD.
CONCLUSIONS: This software offers a means of quantifying the size of PPA on two-dimensional fundus images for the first time. The proposed algorithm is capable of detecting and quantifying PPA and OD regions repeatedly, with a mean accuracy of >93%, and could also provide additional information, such as the transverse and conjugate diameter of OD, which may be useful in eye-screening.
METHODS: The OD region was segmented using the Chan-Vese model with a shape restraint. This region was then removed from the image (OD+PPA), which was cropped in a modified Chan-Vese approach, producing a first-order estimation of the PPA region. Its boundary is subsequently refined by using thresholding, a scanning filter, and multiseed region-growing methods. Dual channels (blue and red) in the red-green-blue space are used to minimize the interference effects of blood vessels and artifacts.
RESULTS: The software was tested on 94 randomly selected images of eyes with PPA from 66 subjects of a well-characterized cohort database. Our proposed algorithm achieved a mean accuracy level of 93.8% (SD 5.26) and 94.0% (SD 5.88) in estimating the size of the PPA and OD respectively, compared with the ground estimate defined by an ophthalmologist. In terms of correlation between the data of the ground estimate and our estimation, we obtained a correlation coefficient of 0.98 for both the PPA and the OD.
CONCLUSIONS: This software offers a means of quantifying the size of PPA on two-dimensional fundus images for the first time. The proposed algorithm is capable of detecting and quantifying PPA and OD regions repeatedly, with a mean accuracy of >93%, and could also provide additional information, such as the transverse and conjugate diameter of OD, which may be useful in eye-screening.