超声图像中胎儿股骨的自动测量
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摘要
提出一种全自动测量胎儿股骨长的方法,利用Frangi滤波器结合灰度信息分割出超声图像中股骨的候选区域,根据候选区域位置、形状信息定位出股骨区域,利用股骨区域的边缘和拟合出的骨架化曲线定位到股骨的端点,并计算得到股骨长.与医生手动测量结果对比,70幅股骨图像的平均测量误差为1.18 mm,表明该方法可准确测量股骨长.
We propose a novel automatic method to measure the fetal femur length. First,the candidate regions containing the femur are detected in the ultrasound image using Frangi filter and gray information. Then,the femur region is localized based on both the shape and position of the candidate regions. Finally,the femur end points are determined by detecting the edges of the femur region and fitting the femur skeleton. The femur length is measured.Comparing with the results measured by doctors,the average measurement error of 70 ultrasound femur images is 1. 18 mm,which indicates that our method can accurately measure the femur length.
We propose a novel automatic method to measure the fetal femur length. First,the candidate regions containing the femur are detected in the ultrasound image using Frangi filter and gray information. Then,the femur region is localized based on both the shape and position of the candidate regions. Finally,the femur end points are determined by detecting the edges of the femur region and fitting the femur skeleton. The femur length is measured.Comparing with the results measured by doctors,the average measurement error of 70 ultrasound femur images is 1. 18 mm,which indicates that our method can accurately measure the femur length.
引文
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[15]Liu Hongzhi,Wu Zhonghai,Zhang Xing,et al.A skeleton pruning algorithm based on information fusion[J].Pattern Recognition Letters,2013,34(10):1138-1145.
[16]Udupa J K,Leblanc V R,Ying Zhuge,et al.A framework for evaluating image segmentation algorithms[J].Computerized Medical Imaging and Graphics,2006,30(2):75-87.
[17]Heimann T,Van Ginneken B,Styner M A,et al.Comparison and evaluation of methods for liver segmentation from CT datasets[J].IEEE Transactions on Medical Imaging,2009,28(8):1251-1265.
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[2]万仪芳,沈国芳,朱家安.超声测量评估胎儿主要生长参数的研究[J].上海医学,2010,33(12):1132-1134.Wan Yifang,Shen Guofang,Zhu Jiaan.Ultrasonography determination in evaluation of major growth parameters of fetuses[J].Shanghai Medical Journal,2010,33(12):1132-1134.(in Chinese)
[3]詹林,文桂琼,林毅,等.产前超声筛查诊断胎儿肢体畸形的价值[J].中国医学影像学杂志,2010,18(3):213-216.Zhan Lin,Wen Guiqiong,Lin Yi.et al.The effectiveness of ultrasound screening in the prenatal diagnosis of fetal malformation[J].Chinese Journal of Medical Imaging,2010,18(3):213-216.(in Chinese)
[4]李威,贾淑文,吕祥.产前超声检查对胎儿畸形的诊断价值[J].中国妇幼保健,2013,28(8):1290-1292.Li Wei,Jia Shuwen,Lv Xiang.The effectiveness of ultrasound screening in the prenatal diagnosis of fetal malformation[J].Maternal and Child Health Care of China,2013,28(8):1290-1292.(in Chinese)
[5]李璟,倪东,李胜利,等.超声图像中胎儿头围的自动测量[J].深圳大学学报理工版,2014,31(5):455-463.Li Jing,Ni Dong,Li Shengli,et al.The automatic ultrasound measurement of fetal head circumference[J].Journal of Shenzhen University Science and Engineering,2014,31(5):455-463.(in Chinese)
[6]Maurits V T,Antti M,Bart K.Repetitive strain injury[J].Lancet,2007,369(9575):1815-1822.
[7]Zhang Lei,Ye Xujiong,Lambrou T,et al.A supervised texton based approach for automatic segmentation and measurement of the fetal head and femur in 2D ultrasound images[J].Physics in Medicine and Biology,2016,61(3):1095-1115.
[8]Wang C W.Automatic entropy-based femur segmentation and fast length measurement for fetal ultrasound images[C]//International Conference on Advanced Robotics and Intelligent Systems.[S.l.]:IEEE,2014:1-5.
[9]余锦华,汪源源,陈萍,等.胎儿超声图像分割及自动径线测量[J].中国生物医学工程学报,2007,26(6):867-873.Yu Jinhua,Wang Yuanyuan,Chen Ping,et al.Fetal ultrasound image segmentation and automatic diameter and length measurement[J].Chinese Journal of Biomedical Engineering,2007,26(6):867-873.(in Chinese)
[10]Salomon L J,Alfirevic Z,Berghella V,et al.Practice guidelines for performance of the routine mid-trimester fetal ultrasound scan[J].Ultrasound in Obstetrics&Gynecology:the Official Journal of the International Society of Ultrasound in Obstetrics and Gynecology,2011,37(1):116-126.
[11]Frangi A F,Niessen W J,Vincken K L,et al.Multiscale vessel enhancement filtering[C]//International Conference on Medical Image Computing and ComputerAssisted Intervention.Berlin:Springer Berlin Heidelberg,2000:130-137.
[12]Jimenez-Carretero D,Santos A,Kerkstra S,et al.3D Frangi-based lung vessel enhancement filter penalizing airways[C]//IEEE the 10th International Symposium on Biomedical Imaging.[S.l.]:IEEE,2013:926-929.
[13]Shashank,Bhattacharya M,Sharma G K.Optimized coronary artery segmentation using Frangi filter and Anisotropic diffusion filtering[C]//International Symposium on Computational and Business Intelligence.New Delhi,India:IEEE,2013:261-264.
[14]吕哲,王福利,常玉清,等.改进的形态学骨架提取算法[J].计算机工程,2009,35(19):23-25.Lv Zhe,Wang Fuli,Chang Yuqing,et al.Improved morphological skeleton extraction algorithm[J].Computer Engineering,2009,35(19):23-25.(in Chinese)
[15]Liu Hongzhi,Wu Zhonghai,Zhang Xing,et al.A skeleton pruning algorithm based on information fusion[J].Pattern Recognition Letters,2013,34(10):1138-1145.
[16]Udupa J K,Leblanc V R,Ying Zhuge,et al.A framework for evaluating image segmentation algorithms[J].Computerized Medical Imaging and Graphics,2006,30(2):75-87.
[17]Heimann T,Van Ginneken B,Styner M A,et al.Comparison and evaluation of methods for liver segmentation from CT datasets[J].IEEE Transactions on Medical Imaging,2009,28(8):1251-1265.
[18]Myles P S,Cui J.Using the Bland-Altman method to measure agreement with repeated measure[J].British Journal of Anaesthesia,2007,99(3):309-311.
[19]Rueda S,Fathima S,Knight C L,et al.Evaluation and comparison of current fetal ultrasound image segmentation methods for biometric measurements:a grand challenge[J].IEEE Transactions on Medical Imaging,?2014,33(4):797-813.
[20]Székely G J,Rizzo M L.The distance correlation t-test of independence in high dimension[J].Journal of Multivariate Analysis,2013,117(3):193-213.