AI imaging · Research-stage prototype

Learning structure.
Reconstructing
detail.

Anatomy-aware AI for one-step accelerated MRI reconstruction. We’re investigating how joint pretraining can help generative models preserve the structures that matter.

Request research access Explore the approach ↓

For researchers and imaging collaborators.

RECONDRIFT / VOLUMETRIC LEARNINGCONCEPT 001
Volumetric anatomy representation schematicLayered contours illustrate a volume moving from acquired measurements toward a structured reconstruction. This is an abstract diagram, not an MRI result.SHARED FEATURESSPATIAL CONTEXT
MEASUREMENTS → REPRESENTATION → IMAGEILLUSTRATIVE SCHEMATIC
One-step generationAnatomical supervisionVolumetric context
01 / The approach

Better reconstruction
starts with what we learn.

Global image scores don’t tell the whole story. Our research focuses on preserving fine anatomical structure through a staged learning process, grounded in the acquired MRI measurements.

01 — MEASURE

A physics-based starting point

Start from undersampled multicoil MRI measurements. A physics-based reconstruction supplies the image estimate that the network learns to refine.

Measurement-conditioned inputs
02 — PRIME

Learn anatomy alongside images

Our planned volumetric setup combines reconstruction and tissue-segmentation supervision to develop shared representations of important structures.

Joint pretraining
03 — REFINE

Reconstruct in one step

Drifting-based post-training refines the generated image distribution while retaining paired reconstruction supervision. The goal is a single-pass reconstruction network.

Distributional post-training
02 / Research direction

Anatomy is more
than image texture.

ReconDrift is an independent research-stage project exploring jointly pretrained drifting models for accelerated MRI reconstruction.

Can learning to identify anatomical structures first help a generative reconstructor preserve them later?
Current work

Evaluating reconstruction pretraining and drifting on slice-based knee MRI prototypes.

Next stage

Developing volumetric reconstruction with Anatomix features and testing segmentation-to-reconstruction transfer.

We assess reconstruction fidelity, local structural detail, measurement agreement, and computational cost. Improved clinical performance remains to be established.

03 / Collaborate

Build toward more faithful imaging.

Interested in reconstruction research, anatomical evaluation, or an early research collaboration? Get in touch to discuss the prototype and access.

Let’s talk