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Evaluation of software for registration of contrast-enhanced brain MR images in patients with glioblastoma multiforme.

作者信息

Barboriak Daniel P, Provenzale James M

机构信息

Department of Radiology, Box 3808, Duke University Medical Center, Durham, NC 27710, USA.

出版信息

AJR Am J Roentgenol. 2002 Jul;179(1):245-50. doi: 10.2214/ajr.179.1.1790245.

DOI:10.2214/ajr.179.1.1790245
PMID:12076945
Abstract

OBJECTIVE

We evaluated commercially available software that rapidly and automatically registers brain MR images on a clinical workstation, and we studied the accuracy of these registrations.

SUBJECTS AND METHODS

Ten patients with a diagnosis of glioblastoma multiforme underwent contrast-enhanced inversion recovery prepared three-dimensional (3D) volumetric spoiled gradient-recalled acquisition in the steady state (SPGR) MR imaging (contiguous 1.5-mm slice thickness, 96-104 slices). After this imaging sequence, each patient was brought out of the head coil into a sitting position and then repositioned in the coil. The inversion recovery prepared 3D SPGR sequence was then repeated. A commercially available software program operating on a clinical workstation was used to automatically register the second inversion recovery prepared SPGR series to the first. The speed of registration was recorded. The accuracy of each registration was estimated by recording the coordinates of eight anatomic landmarks on the registered and reference series and by calculating the mean error among matching landmarks.

RESULTS

In nine of 10 patients, the registration software produced a visually satisfactory registration. In one patient, a second registration was necessary to produce a satisfactory registration. The processing time for each iteration was 48.3 +/- 3.8 sec (mean +/- SD). The mean error in aligning matching anatomic landmarks ranged from 0.67 to 1.41 mm, with an overall mean of 1.18 mm. The largest error among matching landmarks was 2.3 mm.

CONCLUSION

Commercially available registration software can automatically register 3D imaging volumes in less than 1 min. The mean error in registration was approximately equivalent to the dimensions of a single voxel.

摘要

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