Purpose The present study compared manual and automated measurement of Cobb angle in idiopathic scoliosis based on deep learning keypoint detection technology. Methods A total of 181 anterior–posterior spinal X-rays were included in this study, including 165 cases of idiopathic scoliosis and 16 normal adult cases without scoliosis. We labeled all images and randomly chose 145 as the training set and 36 as the test set. Two state-of-the-art deep learning object detection models based on convolutional neural networks were used in sequence to segment each vertebra and locate the vertebral corners. Cobb angles measured from the output of the models were compared to manual measurements performed by orthopedic experts. Results The mean Cobb angle in test cases was 27.4° ± 19.2° (range 0.00–91.00°) with manual measurements and 26.4° ± 18.9° (range 0.00–88.00°) with automated measurements. The automated method needed 4.45 s on average to measure each radiograph. The intra-class correlation coefficient (ICC) for the reliability of the automated measurement of the Cobb angle was 0.994. The Pearson correlation coefficient and mean absolute error between automated positioning and expert annotation were 0.990 and 2.2° ± 2.0°, respectively. The analytical result for the Spearman rank-order correlation was 0.984 (p < 0.001). Conclusion The automated measurement results agreed with the experts’ annotation and had a high degree of reliability when the Cobb angle did not exceed 90° and could locate multiple curves in the same scoliosis case simultaneously in a short period of time. Our results need to be verified in more cases in the future.

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A serial of cerium phosphate/reduced graphene oxide (CePO4-rGO) composites were synthesized for the first time by one-pot hydrothermal method. Structural analyses revealed that flaky CePO4 and few-layer rGO were composited homogeneously. It is found that rGO can greatly enhance the conductivity and the adsorption capacity of the composite. With these advantages, the constructed composites were used for electrochemical detection of dopamine (DA) and acetaminophen (APAP). Further studies show that the loading amount of rGO was also very important. When CePO4-0.6rGO was used, wide linear ranges of 1.2 - 50 µM for DA and 0.5 - 30 µM for APAP can be obtained, respectively. The detection limits of DA and APAP were 0.013 µM and 0.025 µM with high sensitivities of 25.58 μA μM-1 cm-2 and 13.30 μA μM-1 cm-2, respectively. Moreover, the modified electrode also has high selectivity, good stability and satisfactory reproducibility. In addition, the modified electrode was also successfully applied to detect DA and APAP in real urine samples. This work provides a simple method for preparing new electrode materials for detecting small biomolecules.