Evaluation of 3D Ultrasound Reconstruction and 2D/3D Segmentation for Neonatal Hip Dysplasia Screening
Keywords: Hip Dysplasia, Ultrasound, Validation, Segmentation, 3D Reconstruction
TL;DR: Validation study of 3D reconstructed freehand ultrasound for neonatal hip dysplasia screening, comparing 2D and 3D deep-learning–based segmentation methods.
Abstract: Early detection of developmental dysplasia of the hip relies heavily on the correct acquisition and interpretation of ultrasound images. Yet, conventional single-plane imaging provides only a limited view of the neonatal hip, is operator-dependent and sensitive to probe orientation. In this study, we present a clinically oriented validation of a dual-sweep 3D ultrasound approach aimed at improving anatomical coverage and simplifying the diagnostic process. Our dataset comprises 50 optically tracked acquisitions and 150 untracked freehand sweeps from newborns, enabling the reconstruction of volumetric representations of the hip from standard handheld 2D ultrasound. We evaluate 2D and 3D nnU-Net–based segmentation models to quantify how volumetric context influences the delineation of key joint structures. Results demonstrate that the combination of 2D slice-based and 3D volumetric segmentation yields the most robust performance, particularly in cases with anatomical variability or suboptimal sweep direction. The study also highlights remaining challenges, including motion artefacts and inconsistent sweep trajectories, that affect reconstruction quality.
Primary Subject Area: Segmentation
Secondary Subject Area: Image Acquisition and Reconstruction
Registration Requirement: Yes
Reproducibility: https://github.com/MDL-UzL/JOINT
Visa & Travel: No
Read CFP & Author Instructions: Yes
Originality Policy: Yes
Single-blind & Not Under Review Elsewhere: Yes
LLM Policy: Yes
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Latex Code: zip
Copyright Form: pdf
Submission Number: 30
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