@inproceedings{5c1036d69ae24045b1b522f2b38f0b2e,
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.",
keywords = "3D-2D Registration, blind deconvolution, kinematic analysis, quantum noise, Wiener filter",
author = "Masuma Akter and Lambert, {Andrew J.} and Pickering, {Mark R.} and Scarvell, {Jennie M.} and Smith, {Paul N.}",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 ; Conference date: 26-08-2014 Through 30-08-2014",
year = "2014",
month = nov,
day = "2",
doi = "10.1109/EMBC.2014.6944777",
language = "English",
series = "2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "5121--5124",
booktitle = "2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014",
address = "United States",
}