title: 3D CT to 2D low dose single-plane fluoroscopy registration algorithm for in-vivo knee motion analysis.
abstract: A limitation to accurate automatic tracking of knee motion is the noise and blurring present in low dose X-ray fluoroscopy images. For more accurate tracking, this noise should be reduced while preserving anatomical structures such as bone. Noise in low dose X-ray images is generated from different sources, however quantum noise is by far the most dominant. In this paper we present an accurate multi-modal image registration algorithm which successfully registers 3D CT to 2D single plane low dose noisy and blurred fluoroscopy images that are captured for healthy knees. The proposed algorithm uses a new registration framework including a filtering method to reduce the noise and blurring effect in fluoroscopy images. Our experimental results show that the extra pre-filtering step included in the proposed approach maintains higher accuracy and repeatability for in vivo knee joint motion analysis.
authors.forename: Masuma
authors.initials: M
authors.lastname: Akter
authors.forename: Andrew J
authors.initials: AJ
authors.lastname: Lambert
authors.forename: Mark R
authors.initials: MR
authors.lastname: Pickering
authors.forename: Jennie M
authors.initials: JM
authors.lastname: Scarvell
authors.forename: Paul N
authors.initials: PN
authors.lastname: Smith
mesh_terms: D000465:Algorithms; D004307:Dose-Response Relationship, Radiation; D005269:Femur / Q000000981:diagnostic imaging; D005471:Fluoroscopy / Q000379:methods*; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D007719:Knee Joint / Q000000981:diagnostic imaging*; D009038:Motion; D015203:Reproducibility of Results; D013977:Tibia / Q000000981:diagnostic imaging; D014057:Tomography, X-Ray Computed / Q000379:methods*