DiPath provides comprehensive digital pathology solutions, from high-precision whole slide scanners to AI-powered analysis platforms, enabling faster and more accurate cancer diagnoses worldwide.
From slide digitization to AI-powered analysis, we provide end-to-end solutions for modern pathology labs.
High-precision whole slide imaging scanners with exceptional image quality, fast scanning speeds, and seamless integration with AI analysis platforms.
Advanced AI-powered pathology analysis platform with deep learning algorithms for automated detection, classification, and quantification of pathological features.
Precise immunohistochemistry analysis with automated scoring, percentage calculations, and comprehensive reporting for biomarker assessment.
Intelligent cytological screening system for early cancer detection, featuring cell classification, abnormality detection, and quality control automation.
Our proprietary PathGPT engine combines state-of-the-art deep learning architectures with millions of annotated pathology images to deliver unprecedented diagnostic accuracy.
Processes images at multiple magnifications for comprehensive evaluation
Sub-second analysis with GPU-accelerated inference
AI models improve with each case through federated learning
Heatmap visualizations show exactly where AI focuses
PathGPT Engine
See how our solutions are transforming pathology workflows around the world.
"DiPath's AI platform has revolutionized our diagnostic workflow. The accuracy and efficiency gains have been remarkable, reducing our reporting time by 60%."
Dr. Sarah Chen
Chief Pathologist, Peking Union Medical College Hospital
"The VisionX scanner delivers exceptional image quality. Combined with D-PathAI, we've achieved unprecedented diagnostic precision in our oncology department."
Prof. James Mitchell
Director of Pathology, MD Anderson Cancer Center
"Implementing DiPath's IHC quantification module has transformed our biomarker testing. The automated scoring is highly accurate and consistently reliable."
Dr. Lisa Wang
Head of Laboratory Medicine, Shanghai Cancer Center
Hospitals Worldwide
Slides Analyzed
Accuracy Rate
Time Saved
Partnering with global healthcare and technology leaders to advance digital pathology.
Our research has been published in top-tier medical and scientific journals worldwide.
A topology-guided pathology foundation model enabling high-resolution pathology image synthesis with cellular-level control.
A generative foundation AI assistant for pathology, bridging large language models with expert pathology knowledge for diagnostic support.
A novel variational information bottleneck approach for weakly-supervised whole slide image classification in computational pathology.
A landmark deep learning framework achieving pathologist-level accuracy in whole-slide cancer diagnosis with interpretable explanations.
Join thousands of pathologists and healthcare institutions already using DiPath to improve diagnostic accuracy and efficiency.