AI-assisted Gastric Cancer Diagnosis System
About it
The Gastric Biopsy AI-Assisted Diagnostic System is designed for automatic detection and classification of gastric cancer and precancerous lesions.
It addresses key challenges in pathology such as slow lesion localization and difficulty in tumor subtype identification.
By significantly reducing analysis time and supporting structured report generation, it enhances diagnostic accuracy and efficiency while providing standardized data for research.
Multi-Lineage Recognition
Covers gastric carcinoma (adenocarcinoma, mucinous, signet-ring cell), precancerous lesions, and benign conditions.
Precise Tumor Segmentation
Automatically delineates tumor boundaries to assist lesion extent assessment.
High Clinical Consistency
96%+ agreement with pathologists from top hospitals; validated on 50,000+ multi-center slides.
Comprehensive Data Foundation
Trained on 50,000+ slides from 10 hospitals covering diverse gastric sites.
Seamless Report Integration
Generates structured reports with tumor subtype, grade, and heatmap visualization.
Optimized Workflow
Reduces pathologists’ workload and shortens report generation time by up to 80%.
Recognizable Lesion Types
| Primary Category | Secondary Attribute | |
| Positive | Signet Ring Cell Carcinoma | |
| Adenocarcinoma | ||
| High-grade Intraepithelial Neoplasia | ||
| Low-grade Intraepithelial Neoplasia | ||
| Positive | Mild / Moderate / Severe | |
| Negative | Active Inflammation | |
| Chronic Inflammation | Mild / Moderate / Severe | |
| Intestinal Metaplasia | ||
| Atrophy | ||
| Hemorrhage | ||
Powering global digital pathology with performance, scale, and trust
The Numbers Behind Our Innovation
Network and GPU Server Requirements
| Parameter Category | Minimum Requirement | Recommended Configuration | Remarks |
| Local Network Bandwidth | Between server and client ≥100Mbps | Between server and client ≥1Gbps (preferably optical) | Core switch supports ≥10Gbps uplink |
| Network Latency | ≤50ms (between LAN nodes) | ≤20ms (between LAN nodes) | Supports link aggregation (LACP) for improved stability |
| Network Topology | Supports star/tree topology | Supports redundancy (dual-core switch) | Key nodes (e.g., database server) require dual-network binding |
| Interface Type | Client RJ45 (10/100BASE-T) | Server RJ45 (1000BASE-T) + Optical port (optional) | Optical interface supports LC/SC connectors, transmission distance ≤5km |
| Parameter Category | Minimum Requirement | High-Performance Configuration (e.g., AI Training / Rendering) | Remarks |
| GPU Model | NVIDIA 2080Ti ×1 | NVIDIA A4000 ×1 | |
| GPU Memory | 11GB GDDR6 (ECC optional) | 16GB HBM2e (ECC required) | |
| GPU Quantity | Single GPU per host | Single GPU per host | |
| CPU | Intel Xeon E-2274G (4 cores, 8 threads, 3.8GHz) | Intel Xeon E-2274G (8 cores, 16 threads, 3.8GHz) | Main frequency ≥3.0GHz, cache ≥24MB |
| Memory | 32GB DDR4-2666 (ECC) | 64GB DDR5-4800 (ECC Registered) | |
| Storage Interface | 1×NVMe SSD (PCIe 3.0) | 2×NVMe SSD (PCIe 4.0, RAID 0) | Supports hot-swap, continuous read/write ≥3000MB/s |
| Power & Cooling | 900W 80+ Gold PSU, air cooling | 1600W 80+ Platinum PSU, liquid cooling system | |
| OS Compatibility | Supports Ubuntu 22.04 server version | Supports Ubuntu 22.04 server version | Docker pre-installed (ready for container deployment) |
