Automatic classification of kidney stone components based on smartphone microscopy and the GoogLeNet model
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Background: To develop an automated classification system for urinary stone composition by integrating smartphone-based microscopic imaging (TIPSCOPE) with the GoogLeNet architecture, with the goal of enabling rapid, accurate, an... ...
