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Brain Extraction Using Label Propagation and Group Agreement: Pincram

Artikel i vetenskaplig tidskrift
Författare Rolf A. Heckemann
C. Ledig
K. R. Gray
P. Aljabar
D. Rueckert
J. V. Hajnal
A. Hammers
Publicerad i Plos One
Volym 10
Nummer/häfte 7
ISSN 1932-6203
Publiceringsår 2015
Publicerad vid Institutionen för neurovetenskap och fysiologi
Språk en
Länkar dx.doi.org/10.1371/journal.pone.012...
Ämnesord FREE-FORM DEFORMATIONS, AUTOMATIC SEGMENTATION, INTRACRANIAL VOLUME, ATLAS, FUSION, IMAGES, SCANS, Multidisciplinary Sciences
Ämneskategorier Neurovetenskaper

Sammanfattning

Accurately delineating the brain on magnetic resonance (MR) images of the head is a prerequisite for many neuroimaging methods. Most existing methods exhibit disadvantages in that they are laborious, yield inconsistent results, and/or require training data to closely match the data to be processed. Here, we present pincram, an automatic, versatile method for accurately labelling the adult brain on T1-weighted 3D MR head images. The method uses an iterative refinement approach to propagate labels from multiple atlases to a given target image using image registration. At each refinement level, a consensus label is generated. At the subsequent level, the search for the brain boundary is constrained to the neighbourhood of the boundary of this consensus label. The method achieves high accuracy (Jaccard coefficient > 0.95 on typical data, corresponding to a Dice similarity coefficient of > 0.97) and performs better than many state-of-the-art methods as evidenced by independent evaluation on the Segmentation Validation Engine. Via a novel self-monitoring feature, the program generates the " success index," a scalar metadatum indicative of the accuracy of the output label. Pincram is available as open source software.

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