Abstract
Automatic segmentation of ulna and radius (UR) in forearm radiographs is a necessary step for single X-ray absorptiometry bone mineral density measurement and diagnosis of osteoporosis. Accurate and robust segmentation of UR is difficult, given the variation in forearms between patients and the nonuniformity intensity in forearm radiographs. In this work, we proposed a practical automatic UR segmentation method through the dynamic programming (DP) algorithm to trace UR contours. Four seed points along four UR diaphysis edges are automatically located in the preprocessed radiographs. Then, the minimum cost paths in a cost map are traced from the seed points through the DP algorithm as UR edges and are merged as the UR contours. The proposed method is quantitatively evaluated using 37 forearm radiographs with manual segmentation results, including 22 normal-exposure and 15 low-exposure radiographs. The average Dice similarity coefficient of our method reached 0.945. The average mean absolute distance between the contours extracted by our method and a radiologist is only 5.04 pixels. The segmentation performance of our method between the normal- and low-exposure radiographs was insignificantly different. Our method was also validated on 105 forearm radiographs acquired under various imaging conditions from several hospitals. The results demonstrated that our method was fairly robust for forearm radiographs of various qualities.
Highlights
Ulna and radius (UR) are sensitive to changes in a human bone mineral density (BMD) index
Noninvasive BMD measurement methods mainly consist of single X-ray absorptiometry (SXA), dual-energy X-ray absorptiometry, quantitative ultrasound, and quantitative computed tomography [2]. e SXA methods are extensively applied in clinics, and the methods have the advantages of low radiation, easy operation, and low-cost for patients
Accurate and robust extraction of the UR from forearm radiographs is needed in a BMD measurement system of the SXA. e extraction is a challenging task for several reasons
Summary
Ulna and radius (UR) are sensitive to changes in a human bone mineral density (BMD) index. BMD measurements play a crucial role in evaluating patients at risk of osteoporosis [1]. E SXA methods are extensively applied in clinics, and the methods have the advantages of low radiation, easy operation, and low-cost for patients. Accurate and robust extraction of the UR from forearm radiographs is needed in a BMD measurement system of the SXA. E contours of the UR in forearm radiographs are weak, fuzzy, and diffusive near the wrist regions that frequently overlap with other bones and soft tissues. This phenomenon is evident in the forearm radiographs of elderly patients. Clinical forearm radiographs have serious global intensity inhomogeneity
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