Infusion Scene Environment Classification Image Dataset

The current medical industry faces challenges of insufficient image data and low annotation quality in the environmental classification of infusion scenes. Existing solutions largely rely on manual annotation, which is inefficient and prone to errors. This dataset aims to solve image recognition problems in the infusion environment classification by providing high-quality annotated data to meet the needs of clinical decision support and medical image analysis. Data collection uses professional medical imaging equipment, covering infusion scenes in different hospitals to ensure diversity and representativeness. Multiple rounds of review and expert evaluation were implemented during the annotation process to ensure annotation consistency and accuracy. Data is stored in JPG format and organized by category to facilitate subsequent model training and application.