Image dataset of urine test results on petri dishes for deep learning classification.

ABSTRACT: Recent advancements in image analysis and interpretation technologies using computer vision techniques have shown potential for novel applications in clinical microbiology laboratories to support task automation aiming for faster and more reliable diagnostics. Deep learning models can be a valuable tool in the screening process, helping technicians spend less time classifying no-growth results and quickly separating the categories of tests that deserve further analysis. In this context, creating datasets with correctly classified images is fundamental for developing and improving such models. Therefore, a dataset of urine test Petri dishes images was collected following a standardized process, with controlled conditions of positioning and lighting. Image acquisition was conducted by applyi

SUBMITTER: da Silva GR 

PROVIDER: S-EPMC10024077 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature