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

Abstract

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.