GEPAR3D combines a statistical-shape-model prior and 3D deep watershed energy maps to segment teeth and root apices in CBCT, reaching 95.0% average Dice across external test sets.
Nature Communications 13(1), 2096 (2022) 10 T.Szczepański et al
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.IV 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
GEPAR3D: Geometry Prior-Assisted Learning for 3D Tooth Segmentation
GEPAR3D combines a statistical-shape-model prior and 3D deep watershed energy maps to segment teeth and root apices in CBCT, reaching 95.0% average Dice across external test sets.