MuhammadNabeelSh/cephalometry-landmarks

CEPHA29 cephalometric landmark model (HRNet-W32)

29-landmark HRNet-W32 for automatic cephalometric landmark detection, used by Cephalometry Studio for in-browser auto-tracing (ONNX Runtime Web, WASM).

Files

• landmarks-cepha29.int8.onnx — static-QDQ INT8, 768×768×3 input, output [1,29,192,192] (29 heatmaps)
• landmarks-cepha29.onnx — FP32 (same MRE)

Performance (valid split, 150 images)

MRE 1.24 mm · SDR@2mm 83.1% · SDR@3mm 93.7% · SDR@4mm 97.2%

Channel order (must match output index)

A ANS Ar B Co Gn Go LIA LIT LMT LPM Li Ls Me N N Or PNS Pn Po Pog Pog R S Sn UIA UIT UMT UPM

Training

CephaloHRNet (MIT) · HRNet-W32 ImageNet backbone · CEPHA29/Aariz averaged annotations.

Dataset & attribution

Trained on the Aariz Cephalometric Dataset (CEPHA29) — Figshare, CC BY 4.0, DOI 10.6084/m9.figshare.27986417. Training code: CephaloHRNet (MIT). Backbone: HRNet-W32 ImageNet (hrnet_w32.ms_in1k, Apache-2.0).

Disclaimer

Research and education only. Not a medical device; not for diagnosis or treatment.