Bethesda
classification
Micro Solutions / Life Science
AI module for analysis of cervical cytology KFBio LBC Cervical
AI screening of cervical fluid cytology using the Bethesda system with case prioritization
Product overview
- KFBio AI — LBC Cervical
- KFBio
- China
- KFBio AI Models
- LBC Cervical
AI screening of cervical fluid cytology using the Bethesda system with case prioritization
detects HSIL, ASC-H, LSIL, ASC-US and atypical glandular cells
An AI system for pre-testing cervical fluid cytology for mass screening and prioritization of suspicious cases. Automatic drug sorting reduces routine workload and directs the cytologist's attention to the most important cells.
The module classifies drugs by Bethesda, detects HSIL, ASC-H, LSIL, ASC-US and atypical glandular cells, notes suspicious areas and forms a structured report. Trichomonas, Candida, Actinomyces, clue cells and HSV signs are additionally recognized; cases are ranked by risk.
Membrane, sedimentation and centrifuge preparation, images from different manufacturers and integration with LIS are supported. For local installation, KFBio indicates a network from 100 Mbit / s, NVIDIA 2080 Ti GPU level, from 32 GB of RAM and Ubuntu 22.04 server; the recommended configuration is a gigabit network, NVIDIA A4000 and 64 GB of RAM.
Key figures
LICES
integration
GPU
local analysis server
Applications
- Cervical screening
- Liquid cytology
- Oncocytology
- Quality control of cytology
Models and configurations
- LBC Cervical
Product details
AI analysis of cervical cytology
classification
Ranking of cases
prioritization by risk
Analysis opportunities
- Classification of drugs according to the Bethesda system
- Identification of HSIL, ASC-H, LSIL, ASC-US and atypical glandular cells
- Recognition of Trichomonas, Candida, Actinomyces, clue cells and HSV signs
- Ranking of cases by risk
Compatibility
- Support for membrane, sedimentary and centrifuge preparation of drugs
- Work with images of scanners from different manufacturers
- Integration with LIS
Infrastructure
- Local installation: network from 100 Mbit / s, GPU level NVIDIA 2080 Ti, from 32 GB of RAM, Ubuntu server 22.04
- Recommended configuration: Gigabit network, NVIDIA A4000, 64 GB of RAM
Diagnostics
| Classification | Bethesda system |
|---|---|
| Identified changes | HSIL, ASC-H, LSIL, ASC-US, atypical glandular cells |
| It's further recognized. | Trichomonas, Candida, Actinomyces, clue cells, signs of HSV |
Compatibility
| Preparation of drugs | membrane, sedimentary, centrifuge |
|---|---|
| Image sources | scanners from different manufacturers |
| Integration | LICES |
Infrastructure
| Minimum requirements | network from 100 Mbit / s, NVIDIA 2080 Ti GPU, RAM from 32 GB, Ubuntu 22.04 |
|---|---|
| Recommended configuration | Gigabit network, NVIDIA A4000 GPU, 64 GB RAM |
Related equipment types
- Digital slide scanners
- Digital slide management system
- Liquid cytology apparatus
- Staining machines for cytology
Related products
- KFBio KF-DSMS — Digital slide management system
- ELITech Aerospray Gram — Staining machines for cytology
Classification
- Histology and cytology
- AI analysis of cervical fluid cytology
- Cytological equipment
- Screening and digital analysis
- Automated primary screening systems
- KFBio AI — LBC Cervical