title: Fracture Detection in Traumatic Pelvic CT Images.
abstract: Fracture detection in pelvic bones is vital for patient diagnostic decisions and treatment planning in traumatic pelvic injuries. Manual detection of bone fracture from computed tomography (CT) images is very challenging due to low resolution of the images and the complex pelvic structures. Automated fracture detection from segmented bones can significantly help physicians analyze pelvic CT images and detect the severity of injuries in a very short period. This paper presents an automated hierarchical algorithm for bone fracture detection in pelvic CT scans using adaptive windowing, boundary tracing, and wavelet transform while incorporating anatomical information. Fracture detection is performed on the basis of the results of prior pelvic bone segmentation via our registered active shape model (RASM). The results are promising and show that the method is capable of detecting fractures accurately.
authors.affiliation: Department of Computer Science, Virginia Commonwealth University, 401 West Main Street, Richmond, VA 23284, USA.
authors.forename: Jie
authors.initials: J
authors.lastname: Wu
authors.forename: Pavani
authors.initials: P
authors.lastname: Davuluri
authors.forename: Kevin R
authors.initials: KR
authors.lastname: Ward
authors.forename: Charles
authors.initials: C
authors.lastname: Cockrell
authors.forename: Rosalyn
authors.initials: R
authors.lastname: Hobson
authors.forename: Kayvan
authors.initials: K
authors.lastname: Najarian