A Laplace–Hamming Binarization Approach for Second‐Generation HR‐pQCT Rescues Fine Feature Segmentation
Authors' conclusion
Our results suggest that the proposed LH approach produces substantially improved binary masks, reduces proportional bias, and provides greater accuracy and reproducibility in important outcome metrics, all due to more accurate segmentation of the fine features in both trabecular and cortical compartments.
Study context
- Population
- 20 volunteers (9 women, 11 men; aged 23–75 years) with 3 repeat radius and tibia scans; cadaveric structure phantoms (14 radii, 6 tibias) scanned on XCTII and μCT at 24.5 μmplus 20 cadaveric phantoms
- Participants
- 20 volunteers
- Comparison
- Laplace-Hamming (LH) segmentation vs manufacturer's standard Gaussian-based binarization for XCTII
- Outcome
- Accuracy and reproducibility of XCTII structure segmentation
Methodological detailsreproducibility and accuracy, in vivo repeat scans, cadaveric phantom validation against μCT
- Reproducibility and accuracy
- In vivo repeat scans
- Cadaveric phantom validation against μCT
Main finding
As reported in the abstract
- LH rescued fine features evident in grayscale images but omitted or overrepresented (thickened) by the standard approach
- LH significantly reduced error in trabecular BV/TV and Tb.Th vs standard; higher error for Tb.Sp
- LH improved XCTII–μCT correlation for Ct.Po and significantly reduced error in Ct.Po.Dm vs standard
- LH improved precision vs standard for BV/TV, Tb.Th, Ct.Po and Ct.Po.Dm at the radius and for Ct.Po at the tibia
Original publication
A Laplace–Hamming Binarization Approach for Second‐Generation HR‐pQCT Rescues Fine Feature Segmentation. J Bone Miner Res. Published 13 May 2023. doi:10.
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