title: [Multisegmental image fusion of the spine].
abstract: Fusion of medical images is a technique that permits the correlation of homologous anatomical structures in different imaging modalities on the basis of a spatial transformation of the data sets. CT and MRI of the spine provide complementary information of possible relevance for diagnostic and therapeutic decisions. Methods enabling a multisegmental CT-MRI fusion of the spine were developed. These solve the problem of altered spatial relationships of the individual anatomical structures due to differing patient positioning in successive data acquisitions. Routine clinical CT and MRI data of a thoracic section of the spine were obtained and transferred to a PC-workstation. Following segmentation of the CT-data, landmarks for each individual vertebra were defined in the CT and MRI data. For each individual vertebra the algorithm we developed then carried out a rigid registration of the CT information to the MR data. The fused data sets were presented as colour-coded images or on the basis of dynamic variation of transparency. To assess registration precision, fiducial registration errors (FRE) and target registration errors (TRE) were calculated. The algorithm permitted multi-segmental image fusion of the spine. The average time required for defining the landmarks was 22 seconds per landmark for CT, and 34 seconds per landmark for MR. The average FRE was 1.53 mm. The TRE for the vertebrae was less than 2 mm. The colour-coded images were particularly suitable for assessing the contours of the anatomical structures, whereas dynamic variation of the transparency of overlapping CT images enabled a better overall assessment of the spatial relationship of the anatomical structures. The algorithm permits precise multi-segmental fusion of CT and MR of the spine, which was not possible using current fusion-algorithms due to variations in the spatial orientation of the anatomical structures caused by different positioning of the axial skeleton in successive examinations.
authors.affiliation: Abteilungen Neurochirurgie, Medizinische Hochschule Hannover. j.kaminsky@t-online.de
authors.forename: J
authors.initials: J
authors.lastname: Kaminsky
authors.forename: T
authors.initials: T
authors.lastname: Rodt
authors.forename: J
authors.initials: J
authors.lastname: Zajaczek
authors.forename: F
authors.initials: F
authors.lastname: Donnerstag
authors.forename: M
authors.initials: M
authors.lastname: Zumkeller
mesh_terms: D000328:Adult; D000465:Algorithms; D016477:Artifacts; D003196:Computer Graphics; D006801:Humans; D007089:Image Enhancement; D007091:Image Processing, Computer-Assisted; D021621:Imaging, Three-Dimensional; D008159:Lumbar Vertebrae / Q000033:anatomy & histology*; D008279:Magnetic Resonance Imaging; D008297:Male; D008432:Mathematical Computing; D015203:Reproducibility of Results; D012984:Software; D013673:Technology Assessment, Biomedical; D013904:Thoracic Vertebrae / Q000033:anatomy & histology*; D036542:Tomography, Spiral Computed