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Evaluation of a novel elastic registration algorithm for spinal imaging data: A pilot clinical study
Author(s) -
Rashad Ashkan,
Heiland Max,
Hiepe Patrick,
Nasirpour Alireza,
Rendenbach Carsten,
Keuchel Jens,
Regier Marc,
AlDam Ahmed
Publication year - 2019
Publication title -
the international journal of medical robotics and computer assisted surgery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.556
H-Index - 53
eISSN - 1478-596X
pISSN - 1478-5951
DOI - 10.1002/rcs.1991
Subject(s) - computer science , sagittal plane , image registration , computer vision , artificial intelligence , image fusion , position (finance) , vertebra , magnetic resonance imaging , real time mri , rigid transformation , nuclear medicine , image (mathematics) , medicine , radiology , anatomy , finance , economics
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.