Femur segmentation in X-ray image based on improved U-Net

2019 The 5th International Conference on Electrical Engineering, Control and Robotics

无线电电子学;计算机科学

Lianghui, Fan^1 ; Gang, Han Jun^1 ; Yang, Jia^1 ; Bin, Yang^2

School of Computer, Xi'An University of Posts and Telecommunications, Xian Shanxi

710121, China^1

Xi'An Honghui Hospital, Xi'an

710054, China^2

关键词: Absolute deviations;    Ct and mr images;    Loss functions;    Net networks;    Non-linear relationships;    Segmentation results;    Similarity coefficients;    X-ray image;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/533/1/012061/pdf
DOI  :  10.1088/1757-899X/533/1/012061

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

Segmentation of Femur bone from X-ray images is an indispensable step in computer aided analysis of medical images and orthopaedic examinations. It is more complex than segmentation from CT and MR images, due to some associated less dense tissues that are hard to distinguish from the femur bone in X-ray images. This paper presents an improved method based on U-Net to automatically extract the femurs from hip X-ray images. This method changes the structure of the U-Net network, which can effectively map the non-linear relationship between hip image and femur image, and accurately segment femur image. The paper also added the absolute deviation loss function to improve the segmentation effect. Experimental results show that this method is accurate, robust, and achieves an average dice similarity coefficient of 0.966. The segmentation results are satisfactory.