Clinical-grade AI imaging analysis for MRI, CT, and X-ray - built for real hospital workflows.
MedPulsar is not a general-purpose computer vision system. Every model is trained exclusively on annotated radiology data, validated in clinical settings, and calibrated to the sensitivity and specificity thresholds real radiologists require.
The platform integrates with your existing PACS infrastructure via standard DICOM protocols. There is no proprietary hardware to install and no workflow re-engineering required. Deployment takes days, not months.
Request a DemoSix core capabilities that make MedPulsar a complete clinical AI solution, not just another screening tool.
Ensemble models combining convolutional and transformer architectures, trained on 14 million annotated scans from partner hospitals across four countries.
DICOM ingestion, preprocessing, normalization, and results export happen automatically. No manual data preparation required by your team.
End-to-end encryption, role-based access controls, full audit trails, and optional on-premise deployment for institutions with strict data residency requirements.
Cloud-native architecture scales horizontally to handle peak imaging volumes. Supports single-site clinics and multi-hospital networks equally.
Centralized management console for network-wide deployment. Roll out updates, configure thresholds, and view performance metrics across all sites from one dashboard.
GPU-optimized inference delivers results in under one second per scan on standard radiology workstation hardware, with no cloud dependency if preferred.
Dedicated models for each imaging modality, trained and validated independently to maximize clinical accuracy.
Brain, spine, and musculoskeletal MRI with anomaly detection across T1, T2, FLAIR, and DWI sequences.
Chest, abdominal, and neurological CT reads with automated lesion segmentation and Hounsfield unit analysis.
Pneumonia, nodule, effusion, and cardiomegaly screening on plain radiographs with structured reporting output.