Infiltration Staining Technology: Utilizes a columnar infiltration staining process to automate Gram staining, suspending the slide for efficient stain consumption. The resulting images feature a clear background, with distinct bacterial and cellular coloration, aiding identification and classification.

Position Tracking Technology: Scans at low magnification (20X) to locate small targets, calculating precise locations in densely packed areas. When switched to oil immersion (100X), the system quickly locates target areas using coordinate tracking, enabling magnification and multi-layered image acquisition, improving detection speed while ensuring no pathological components are missed.

Microscope Automated Control Technology: Combines precision motors with dedicated control algorithms, ensuring sub-micron movement precision. Paired with a high-resolution CCD imaging system, it enables high-precision focusing scans, ensuring fine structures of cells and bacteria are clearly presented.

Intelligent Analysis Technology: Based on convolutional neural networks (CNN) and deep learning methods, paired with intelligent image acquisition technology. By leveraging massive datasets and multi-layer iterative learning, a deep learning model for recognizing vaginal secretions has been developed. The model progressively extracts shallow, mid-level, and deep features, enhancing robustness and generalization capabilities.