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Holden, M.* ; Schnabel, J.A.* ; Hill, D.L.G.*

Quantification of small cerebral ventricular volume changes in treated growth hormone patients using nonrigid registration.

IEEE Trans. Med. Imaging 21, 1292-1301 (2002)

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Open Access Green as soon as Postprint is submitted to ZB.

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Nonrigid registration can automatically quantify small changes in volume of anatomical structures over time by means of segmentation propagation. Here, we use a nonrigid registration algorithm based on optimising normalized mutual information to quantify small changes in brain ventricle volume in magnetic resonance (MR) images of a group of five patients treated with growth hormone replacement therapy and a control group of six volunteers. The lateral ventricles are segmented from each subject image by registering with the brainweb image which has this structure delineated. The mean (standard deviation) volume change measurements are 1.09 (0.73) cm3 for the patient group and 0.08 (0.62) cm3 for the volunteer group; this difference is statistically significant at the 1% level. We validate our volume measurements by determining the precision from three consecutive scans of five volunteers and also comparing the measurements to previously published volume change estimates obtained by visual inspection of difference images. Results demonstrate a precision of σ ≤ 0.52 cm3 (n = 5) and a rank correlation coefficient with assessed difference images of ρ = 0.7 (n = 11). To determine the level of shape correspondence we manually segmented subject's ventricles and compared them to the propagations using a voxel overlap similarity index, this gave a mean similarity index of 0.81 (n = 7).

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Publication type Article: Journal article

Document type Scientific Article

Corresponding Author

Keywords Brain Ventricle Volume Change ; Growth Hormone Replacement Therapy ; Mutual Information ; Nonrigid B-spline Registration ; Segmentation Propagation

ISSN (print) / ISBN 0278-0062

e-ISSN 1558-254X

Journal IEEE Transactions on Medical Imaging

Quellenangaben Volume: 21, Issue: 10, Pages: 1292-1301

Publisher Institute of Electrical and Electronics Engineers (IEEE)

Publishing Place New York, NY [u.a.]

Non-patent literature Publications

Reviewing status Peer reviewed

Institute(s) Institute for Machine Learning in Biomed Imaging (IML)