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Spatial decision forests for MS lesion segmentation in multi-channel magnetic resonance images

Geremia, Ezequiel ; Clatz, Olivier ; Menze, Bjoern H ; Konukoglu, Ender ; Criminisi, Antonio ; Ayache, Nicholas

NeuroImage, 15 July 2011, Vol.57(2), pp.378-390 [Tạp chí có phản biện]

ISSN: 1053-8119 ; E-ISSN: 1095-9572 ; DOI: 10.1016/j.neuroimage.2011.03.080

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  • Nhan đề:
    Spatial decision forests for MS lesion segmentation in multi-channel magnetic resonance images
  • Tác giả: Geremia, Ezequiel ; Clatz, Olivier ; Menze, Bjoern H ; Konukoglu, Ender ; Criminisi, Antonio ; Ayache, Nicholas
  • Chủ đề: Multi-Sequence Mri ; Segmentation ; Multiple Sclerosis ; Random Forests ; Miccai Grand Challenge 2008 ; Medicine
  • Là 1 phần của: NeuroImage, 15 July 2011, Vol.57(2), pp.378-390
  • Mô tả: A new algorithm is presented for the automatic segmentation of Multiple Sclerosis (MS) lesions in 3D Magnetic Resonance (MR) images. It builds on a discriminative random decision forest framework to provide a voxel-wise probabilistic classification of the volume. The method uses multi-channel MR intensities (T1, T2, and FLAIR), knowledge on tissue classes and long-range spatial context to discriminate lesions from background. A symmetry feature is introduced accounting for the fact that some MS lesions tend to develop in an asymmetric way. Quantitative evaluation of the proposed methods is carried out on publicly available labeled cases from the MICCAI MS Lesion Segmentation Challenge 2008 dataset. When tested on the same data, the presented method compares favorably to all earlier methods. In an a posteriori analysis, we show how selected features during classification can be ranked according to their discriminative power and reveal the most important ones. ►...
  • Ngôn ngữ: English
  • Số nhận dạng: ISSN: 1053-8119 ; E-ISSN: 1095-9572 ; DOI: 10.1016/j.neuroimage.2011.03.080

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