Innovation Pipeline

Research Projects

Discover our active, grant-funded, and open-source clinical AI research projects across 3D computer vision, digital pathology, and multimodal model guidance.

Clinical Trial Grant Funded ($1.8M)

CardioVision-Net: Real-Time Echocardiogram Segmentation

Lead: Dr. Sarah Chen

Developing lightweight neural networks deployable on point-of-care cardiac ultrasound devices for low-resource clinics and emergency response teams.

PyTorch Ultrasound Real-Time Inference

Cardiovascular AI Details →

Model Development NIH Sponsored ($2.4M)

NeuroSynth-3D: Synthetic Brain MRI Generation

Lead: Prof. Michael Zhang

Generative 3D diffusion models capable of producing privacy-preserving synthetic dataset extensions for rare neurodegenerative disease research.

Diffusion Models 3D Volumetric MRI Synthetic Data

3D Computer Vision Details →

Ongoing Industry Partnered

PathoScan-AI: Gigapixel Histology Biomarker Profiling

Lead: Dr. Elena Rostova

Foundation vision transformer models trained on over 50,000 whole-slide biopsies for rapid automated cancer grading and margin profiling.

Vision Transformers Gigapixel WSI Digital Pathology

Digital Pathology Details →

Ongoing Grant Funded ($1.2M)

OmniVision-3D: Self-Supervised Vision Transformers for Volumetric Scans

Lead: Dr. Sarah Chen

Pre-training 3D transformers on 150,000 unannotated volumetric scans for zero-shot tumor detection and organ segmentation.

Self-Supervised 3D CT/MRI Transformers

3D Computer Vision Details →

Clinical Trial Clinical Trial Grant

Real-Time Point-of-Care Ultrasound Guidance AI

Lead: Prof. Michael Zhang

Point-of-care mobile neural networks assisting emergency doctors in cardiac ultrasound probe placement and instant view classification.

Point-of-Care Cardiac Ultrasound Mobile AI

Clinical AI Details →