title: Automatic spine curvature estimation from X-ray images of a mouse model.
abstract: Automatic segmentation and quantification of skeletal structures has a variety of applications for biological research. Although solutions for good quality X-ray images of human skeletal structures are in existence in recent years, automatic solutions working on poor quality X-ray images of mice are rare. This paper proposes a fully automatic solution for spine segmentation and curvature quantification from X-ray images of mice. The proposed solution consists of three stages, namely preparation of the region of interest, spine segmentation, and spine curvature quantification, aiming to overcome technical difficulties in processing the X-ray images. We examined six different automatic measurements for quantifying the spine curvature through tests on a sample data set of 100 images. The experimental results show that some of the automatic measures are very close to and consistent with the best manual measurement results by annotators. The test results also demonstrate the effectiveness of the curvature quantification produced by the proposed solution in distinguishing abnormally shaped spines from the normal ones with accuracy up to 98.6%.
authors.affiliation: Department of Applied Computing, University of Buckingham, Buckingham, MK18 1EG, UK.
authors.forename: Omar Al
authors.initials: OA
authors.lastname: Okashi
authors.affiliation: Department of Applied Computing, University of Buckingham, Buckingham, MK18 1EG, UK.
authors.forename: Hongbo
authors.initials: H
authors.lastname: Du
authors.affiliation: Department of Applied Computing, University of Buckingham, Buckingham, MK18 1EG, UK. Electronic address: hisham.al-assam@buckingham.ac.uk.
authors.forename: Hisham
authors.initials: H
authors.lastname: Al-Assam
mesh_terms: D000818:Animals; D004195:Disease Models, Animal; D051379:Mice; D012600:Scoliosis / Q000000981:diagnostic imaging*; D013131:Spine / Q000033:anatomy & histology / Q000000981:diagnostic imaging*; D014965:X-Rays
keywords: Classification; Curvature; Segmentation; Spine; X-ray