Fig. 3
From: Deep learning based quantitative cervical vertebral maturation analysis
The proposed framework (CVnet) for automatic quantitative cervical vertebral maturation analysis on input lateral cephalometric images. (A) The architecture of the landmark location network which firstly detects 3 ROIs of the second, third and fourth cervical vertebra (C2, C3, C4) and then locates landmarks on the sub-images of C2, C3 and C4. (B) Landmark definition and measurements for QCVM analysis. (C) The architecture of the QCVM determination network, the input is 7 measurements (α2, α3, α4, H3/W3, H4/W4, AH3/PH3, AH4/PH4), and the output is the classification of CS1 ∼ 6