Clinical AI Models for Medical Imaging
From anatomy segmentation to critical condition detection — MedBelAI delivers production-ready AI models built on high-quality medical data and clinical expertise.
- Model + inference pipeline (API / SDK)
- Validation report & performance summary
- Clinical integration support (PACS / DICOM workflows)
- Optional: dataset & labeling specification
AI Model Products
Choose a ready-to-customize model or request a tailored pipeline for your modality, anatomy, and clinical objective.
High-precision organ segmentation for quantitative imaging, surgical planning, and downstream detection tasks.
- Brain: cortex, ventricles, vessels
- Thorax: lung lobes, airway, heart chambers
- Abdomen: liver, kidney, pancreas, spleen
- Pelvis: uterus, ovary, prostate, bladder
- Whole-body multi-organ segmentation
Detection models designed for urgent conditions to support triage, prioritization, and clinical decision-making.
- Brain aneurysm detection & segmentation
- Aortic aneurysm and dilation detection
- Acute hemorrhage & ischemic stroke screening
- Pulmonary embolism & vascular abnormality detection
Robust detection and classification pipelines for screening, oncology workflows, and longitudinal monitoring.
- Lung lesions & nodules (CT / X-ray)
- Breast lesions (Mammography / MRI)
- Thyroid nodules (US / CT)
- Uterine & ovarian lesion detection
- Multi-lesion detection across organs
Foundation Models for Medical Imaging
Build or fine-tune imaging foundation models with self-supervised pretraining, weak supervision, and hospital-specific adaptation. Reduce labeling cost, accelerate downstream model development, and improve generalization across scanners and sites.
- Faster model iteration with fewer labeled samples
- Higher robustness across devices and protocols
- Reusable backbone for multiple downstream products
- De-identification & QA pipelines
- Controlled access, secure transfer, audit trails
- Alignment with GDPR / HIPAA operational requirements
Product Matrix
A quick overview of models, modalities, outputs, and typical use cases.
| Model | Modality | Output | Use case |
|---|---|---|---|
| Multi-organ Segmentation | CT, MRI | 2D/3D masks, organ volumes | Quantitative imaging, surgical planning, downstream detection |
| Brain Anatomy Segmentation | MRI, CT | Structure masks (ventricles, cortex), metrics | Neuro analytics, treatment monitoring, research |
| Brain Aneurysm Detection | CTA, MRA | Candidate regions, probability map, optional segmentation | Emergency triage, radiology workflow prioritization |
| Aortic Aneurysm & Dilation | CT, CTA | Diameter measurements, alert flags, optional segmentation | Screening, follow-up monitoring, reporting support |
| Lung Nodule Detection | CT, X-ray | Bounding boxes/centroids, scores, optional segmentation | Screening, oncology support, longitudinal comparison |
| Breast Lesion Detection | Mammography, MRI | Lesion candidates, malignancy scoring | Screening, second-reader support |
| Thyroid Nodule Detection | Ultrasound, CT | Nodule detection + classification | Endocrine screening, report assistance |
| Pelvic Lesion Detection | MRI, Ultrasound | Lesion candidates, segmentation optional | Gynecology workflows, treatment monitoring |
| Foundation Model Fine-tuning | Multi-modality | Backbone weights + downstream head | Private adaptation, faster product development |
Research & Publication Collaboration
We collaborate with hospitals, startups, and research teams to validate models, publish results, and translate research outcomes into market-ready clinical AI products.
- Benchmarking, ablation studies, and external validation design
- Multi-center data strategy and protocol harmonization
- Manuscript support: figures, metrics, reproducibility artifacts
- Marketing-ready research highlights (with partner approval)
- PACS/RIS-friendly workflows and DICOM support
- API/SDK delivery and deployment guidance
- Performance monitoring and continuous improvement loop