Advancing Bag-of-Visual-Words Representations for Lesion Classification in Retinal Images

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Diabetic Retinopathy (DR) is a complication of diabetes that can lead to blindness if not timely discovered. Automated screening algorithms have the potential to improve identification of patients who need further medical attention. However, the identification of lesions must be accurate to be useful for clinical application. The bag-of-visual-words (BoVW) algorithm employs a maximum-margin classifier in a flexible framework that is able to detect the most common DR-related lesions such as micro

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Diabetic Retinopathy (DR) is a complication of diabetes that can lead to blindness if not timely discovered. Automated screening algorithms have the potential to improve identification of patients who need further medical attention. However, the identification of lesions must be accurate to be useful for clinical application. The bag-of-visual-words (BoVW) algorithm employs a maximum-margin classifier in a flexible framework that is able to detect the most common DR-related lesions such as micro