pelvitect-seg — Pediatric Pelvic Segmentation (SegFormer-B3)
Part of the Pelvitect framework for automated analysis of developmental dysplasia of the hip (DDH) from anteroposterior pelvic radiographs.
Model description
SegFormer-B3 fine-tuned on PelviSet (10.5281/zenodo.20615290), a unified
dataset of 14,622 pediatric pelvic radiographs with 12-class anatomical
segmentation masks. The model predicts pixel-level anatomical structures used
downstream by the Pelvitect geometry engine to compute clinical measurements
(acetabular index, center-edge angle, Tönnis grade, IHDI grade, Shenton line).
Label schema (13 classes including background)
| Index | Structure |
|---|---|
| 0 | Background |
| 1 | Right ilium |
| 3 | Right obturator foramen |
| 5 | Right pubis |
| 7 | Right ischium |
| 9 | Right femoral head |
| 11 | Right proximal femur |
Recommended usage
# Via Pelvitect (recommended — handles full pipeline)
from pelvitect import Pelvitect
import numpy as np
from PIL import Image
img = np.array(Image.open("xray.png").convert("RGB"))
result = Pelvitect(image=img).analyze()
print(result.summary())
# Mask only (no keypoints)
from pelvitect.analyzer import SegmentationMasker
masker = SegmentationMasker() # downloads this repo automatically
mask = masker.predict_mask(img) # (H, W) uint8, values 0-12
lm, shenton = masker.derive_all(mask) # geometry landmarks + Shenton arcs
Training details
- Base model:
nvidia/segformer-b3-finetuned-ade-512-512 - Dataset: PelviSet — MTDDH DS1+DS2 (real masks) + USTC-DDH + AV-DDH (pseudo-labeled via iterative nnUNet v2 pipeline with Bridge-IoU gates)
- Real mask training cases: 1,857
- Expanded corpus: 13,980 cases (real + pseudo-labeled)
- Horizontal flip disabled: laterality-aware training (flip would swap right/left labels, causing training collapse)
- Input size: 512 × 512 (resized by SegformerImageProcessor)
Citation
@dataset{pelviset2025,
author = {Mahdavikia, Amir M.},
title = {PelviSet: A Unified Pediatric Pelvic Radiograph Dataset},
year = {2025},
doi = {10.5281/zenodo.20615290},
}