Classification of Outer Retinal Layers Based on KNN-Classifier

Eyes are the organs of the visual system. The eyes are affected by eye diseases causing loss of vision. Retinitis Pigmentosa is a genetic condition which is passed down to families and it varies from person to person. Segmentation (Automatic) of external retinal layers is challenging because of the resolution of the human eye. This paper proposes a technique to classify the external retinal layers by means of KNN. It helps doctors to plan on further treatment. To segment the external layers in the retina by applying different preprocessing steps. To detect the region of interest(outer retina) the pre-processing step is performed. Second, few Framework parameters of the outer retina are calculated by fitting the candidate models. To select the Framework supported by the data Framework resolution technique is required by model selection. The detected layers are assigned by the labels (layer identification). Finally, classification by (KNN) to decide whether or not the eye's is in normal or in abnormal condition.

[1]  Jelena Novosel,et al.  Segmentation of Locally Varying Numbers of Outer Retinal Layers by a Model Selection Approach , 2017, IEEE Transactions on Medical Imaging.

[2]  R. Graczyk The eye. , 1955, Radiography.

[3]  R. Bhadra,et al.  NIH Public Access , 2014 .

[4]  S. Boppart Optical coherence tomography: technology and applications for neuroimaging. , 2003, Psychophysiology.

[5]  Donald C Hood,et al.  The transition zone between healthy and diseased retina in patients with retinitis pigmentosa. , 2011, Investigative ophthalmology & visual science.

[6]  Jelena Novosel,et al.  Method for segmentation of the layers in the outer retina , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[7]  S. Ferrucci,et al.  Retinitis pigmentosa inversa. , 1998, Optometry and vision science : official publication of the American Academy of Optometry.