Hierarchical local binary pattern for branch retinal vein occlusion recognition with fluorescein angiography images
Branch retinal vein occlusion (BRVO) is one of the most common retinal diseases. Without timely diagnosis and treatment, it would seriously impair the patient's vision. Automatic recognition of BRVO could significantly improve the efficiency of diagnosis. A feature representation method is proposed for the automatic recognition of BRVO with fluorescein angiography (FA) images. The proposed feature representation method, termed hierarchical local binary pattern (HLBP), is comprised of LBPs in a hierarchical fashion with max-pooling. A FA image dataset is established to evaluate the performance of the HLBP method. Experimental results demonstrate the superior performance of the proposed HLBP method for BRVO recognition with FA images, by comparing it with state-of-the-art methods.
