  In clinical settings, the screening, diagnosis, and monitoring of adolescent
idiopathic scoliosis (AIS) typically involve physical or radiographic
examinations. However, physical examinations are subjective, while radiographic
examinations expose patients to harmful radiation. Consequently, we propose a
pipeline that can accurately determine scoliosis severity. This pipeline
utilizes posteroanterior (PA) and lateral (LAT) RGB images as input to generate
spine curve maps, which are then used to reconstruct the three-dimensional (3D)
spine curve for AIS severity grading. To generate the 2D spine curves
accurately and efficiently, we further propose an Efficient U-shape transFormer
(EUFormer) as the generator. It can efficiently utilize the learned feature
across channels, therefore producing consecutive spine curves from both PA and
LAT views. Experimental results demonstrate superior performance of EUFormer on
spine curve generation against other classical U-shape models. This finding
demonstrates that the proposed method for grading the severity of AIS, based on
a 3D spine curve, is more accurate when compared to using a 2D spine curve.
