LeaRes turns CT and MRI into patient-specific functional twins: lungs, heart and vessels reconstructed, ventilation and flow simulated, in the browser, on your hospital’s GPU.
All MedLea solutions are browser-accessible and comply with GDPR · HIPAA · SOC2 · EU AI Act.
Longitudinal data hides correlations no reader can hold in mind at once. LeaRes derives the morphofunctional biomarkers, keeps them comparable from scan to scan, and leaves the judgement where it belongs.
Lobes, airway tree and vessels reconstructed from the CT by AI agents, then set in motion: airflow simulated in every airway, regional ventilation in every lobe, on the same anatomy you would take to the operating room.
The breathing twin yields regional biomechanics: where the lung inflates, where it over-distends, how the two lungs share the breath. Maps and AI-derived biomarkers you can read on the familiar MPR views, for ICU and surgical research.
Pulmonary arteries and veins, heart and aorta reconstructed alongside the lungs. The geometry a flow study needs, ready for perfusion research in functional radiology.
Engineering
The engineering workspace takes the reconstructed anatomy, or an imported CAD geometry, sets materials and boundary conditions, and runs the flow. The full solver for the final answer; surrogates for the exploration.
A lattice-Boltzmann multiphysics solver on GPU computes airflow, pressure and particle transport in the patient’s own airways and vessels.
AI surrogates trained on full CFD runs return the same quantities in a fraction of the time, so settings and device variants can be explored interactively before the full solver confirms the final case.
Catheters, stents, flow diverters and ventilator circuits placed in the reconstructed anatomy or imported as CAD, with inlets, outlets and materials set in the browser.
Active Learning
Name the pattern, annotate inside LeaRes, train on your GPU, correct what the model proposes. Each round leaves less to correct. The data never leaves the hospital.
How the platform worksAn agentic workflow that takes a scan through segmentation, reconstruction and simulation.
LeaFlow is Medlea's agentic workflow. AI agents carry a CT or MRI scan through segmentation, anatomical reconstruction and simulation set-up, step by step. At its core sits a multiphysics simulation engine: it models how blood, air, urine, drugs, contrast agents and particles move through the patient's anatomy, and how a medical device — catheter, implant, inhaler, stent — changes that flow. Device and tissue can move and deform together, so a clinician can rehearse a procedure and a device maker can test a prototype in a virtual patient before building it.
Aerosol therapy, nebulisers and smart inhalers: LeaFlow follows the particles through moving airways and shows where they deposit and how much of the dose is exhaled.
Stents, grafts and valves: LeaFlow measures their effect on local flow, wall shear stress and downstream perfusion, inside the vessels of the individual patient.
Ureteral stents, catheters and artificial sphincters: LeaFlow shows how they change urinary flow, pressure gradients and the transport of sediments and particles.
CT and MRI scans become accurate 3D models: airways, vessels, renal tracts and other flow-relevant anatomy are identified and reconstructed automatically, case by case.
Patient models move in and out of standard CAD tools. Engineers place a stent, valve or catheter in real anatomy; surgeons review the same placement beforehand.
LeaFlow runs in the cloud or on premises, on GPUs, for real-time or batch simulations, and every step is driven from an ordinary web browser.
