基于Softmax回归模型的骨龄X射线图像手骨分割

针对儿童青少年的骨骼发育情况，临床上常采用手腕骨X射线图像进行骨龄评估。其中手骨区域的分割是预处理中的关键一步，手骨分割的准确率极大地影响最后的评估结果。传统的阈值分割方法在自动化分割过程中鲁棒性较差，利用深度神经网络的自动分割准确率比传统方法高但较为复杂。研究在阈值分割的基础上，提出先通过训练Softmax回归模型预测最佳阈值得到二值图像，再利用区域生长法提取完整手形，最后对手骨图像进行归一化处理的分割方法。在100张临床数据测试集上，将提出的方法与传统的阈值分割方法——Otsu、最大熵阈值和直方图均值分割方法进行对比，采用相似系数DSC（dice similarity coefficient）、欠分割率和过分割率3个客观评价指标对分割结果进行定量分析。实验证明该方法的分割效果最理想，平均DSC值为0.97，欠分割率和过分割率接近于0，对于复杂的手骨图像也表现出良好的分割性能，相比传统的阈值分割方法具有更好的鲁棒性，能够准确的对骨龄X射线图像进行自动化手骨分割处理。

Hand bone segmentation of skeletal age X-Ray image based on Softmax regression model

X-ray images of wrist bone are often used for clinical bone age assessment to focus on skeletal development in children and adolescents. Among the process, the segmentation of the hand bone region is a key step in the preprocessing, and the accuracy of hand bone segmentation greatly influences the final evaluation results. The traditional threshold segmentation methods have poor robustness in the automatic segmentation process, while using the deep neural network is more accurate but really complex. Aiming at these problems, this paper proposed to predict the optimal threshold by training Softmax regression model to obtain binary image based on threshold segmentation, then use the region growing to extract the whole hand, and normalize the processed images in the end. On the 100 test sets, the proposed method was compared with the traditional threshold segmentation methods-Otsu, maximum entropy threshold and histogram mean segmentation. DSC (dice similarity coefficient), under-segmentation rate and over-segmentation rate were used to quantitatively analyze the results. The experimental results show that the method has achieved the best results with an average DSC value of 0.97, and the under-segmentation rate and the over-segmentation rate are both close to 0. It also shows good performance for complex hand radiographs, which is proved to be more robust than the traditional threshold segmentation methods and can accurately complete automatic hand bone segmentation on skeletal age X-ray images.