Deep learning classification of urinary sediment crystals with optimal parameter tuning.

ABSTRACT: The examination of urinary sediment crystals, the sedimentary components of urine, is useful in screening tests, and is always performed in medical examinations. The examination of urinary sediment crystals is typically done by classifying them under a microscope. Although automated analyzers are commercially available, manual classification is required, which is time-consuming and varies depending on the technologist performing the test and the laboratory. A set of test images was created, consisting of training, validation, and test images. The training images were transformed and augmented using various methods. The test images were classified to determine the patterns that could be correctly classified. Convolutional neural networks were used for training. Furthermore, we also consider

SUBMITTER: Nagai T 

PROVIDER: S-EPMC9729224 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature