摘要
提出一种基于最大熵分割的胎儿股骨自动测量方法。首先,用中值滤波器对原始图像进行去噪,并用最大熵分割方法对去噪后的图像进行分割,得到股骨候选区域;其次,利用股骨区域位置、形状等特征信息对股骨候选区域进行筛选,得到最终的股骨区域;最后,通过股骨区域的外接矩形斜边长,计算股骨长度;与医生手动测量结果对比,70幅超声图像的自动测量结果平均相对误差为1.42±4.48 mm,实验结果验证了本方法的可行性。
To propose a novel automatic method to measure the fetal femur length.First,the candidate regions containing the femur were detected in the ultrasound image using maximum entropy segmentation and gray information.Then the femur region was localized based on both the shape and position of the candidate regions.Finally,the femur end points were detected by hypotenuse of enclosing rectangle of femur and the femur length was measured.Comparing with the results measured by doctors,the average error of 70 ultrasound femur images is 1.42±4.48 mm,which indicates our method can accurately measure the femur length.
出处
《生物医学工程研究》
北大核心
2017年第3期197-200,共4页
Journal Of Biomedical Engineering Research
基金
国家自然科学基金资助项目(6157010571)
关键词
超声
图像处理
股骨长测量
自动测量
最大熵分割
Ultrasound
Image processing
Femur length measurement
Automatic measurement
Maximum entropy segmentation