EchoAppearance: Rebuilding the Vendor Echo Look From Raw Beams
A 117k-parameter CNN turns native beamspace B-mode into GE-style display frames, and shows how a processing mismatch breaks segmentation.
November 8, 2026
Guides, project breakdowns, and lessons learned from building medical imaging platforms — written by the PYCAD team.
A 117k-parameter CNN turns native beamspace B-mode into GE-style display frames, and shows how a processing mismatch breaks segmentation.
Generated labels for 35,838 public T1 scans, each with seven quality checks and a tier, so you can drop bad cases before training.
An automated pass labels the aorta. A language model then picks among candidate fixes drawn on the CT, at under half the agent cost.
One annotated case adapts a LoRA. BrainGFM then synthesizes image-mask pairs, class images, and sequence transforms for MRI and CT.
R231 drops cavities and consolidations on severe TB CT. LungMend fills them from a healthy shape prior and bone cues.
A 3D U-Net predicts virtual CE from non-contrast breast MRI. NC+VCE reaches AUROC 0.901; about 40% of patients could skip acquired CE.
We build custom medical imaging platforms — advanced DICOM viewers, AI segmentation, and the clinical systems around them.
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