Evaluation of a novel elastic registration algorithm for spinal imaging data: A pilot clinical study. Issue 3 (4th March 2019)

• Record Type: Journal Article
• Authors: Rashad, Ashkan; Heiland, Max; Hiepe, Patrick; Nasirpour, Alireza; Rendenbach, Carsten; Keuchel, Jens; Regier, Marc; Al‐Dam, Ahmed
• Is Part Of: International journal of medical robotics and computer assisted surgery. Volume 15:Issue 3(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-03-04
• Subjects: cervical spine -- co‐registration accuracy -- CT -- deformable registration -- elastic fusion -- image registration -- MRI -- rigid fusion -- spine curvature correction; Robotics in medicine -- Periodicals; Surgery -- Technological innovations -- Periodicals; Imaging systems in medicine -- Periodicals; 617.90285
• DOI: 10.1002/rcs.1991
• Languages: English
• ISSNs: 1478-5951

Abstract

Abstract: Background: Rigid image coregistration is an established technique that allows spatial aligning. However, rigid fusion is prone to deformation of the imaged anatomies. In this work, a novel fully automated elastic image registration method is evaluated. Methods: Cervical CT and MRI data of 10 patients were evaluated. The MRI was acquired with the patient in neutral, flexed, and rotated head position. Vertebrawise rigid fusions were performed to transfer bony landmarks for each vertebra from the CT to the MRI space serving as a reference. Results: Elastic fusion of 3D MRI data showed the highest image registration accuracy (target registration error of 3.26 mm with 95% confidence). Further, an elastic fusion of 2D axial MRI data (<4.75 mm with 95% c.) was more reliable than for 2D sagittal sequences (<6.02 mm with 95% c.). Conclusions: The novel method enables elastic MRI‐to‐CT image coregistration for cervical indications with changes of the head position.