3D reconstruction of medical images from slices automatically landmarked with growing neural models

NEUROCOMPUTING

卷:150

Article

Angelopoulou, Anastassia¹  Psarrou, Alexandra¹  Garcia-Rodriguez, Jose²  Orts-Escolano, Sergio²  Azorin-Lopez, Jorge²  Revett, Kenneth³ 

[1] Univ Westminster, Fac Sci & Technol, Cavendish W1W 6UW, England

[2] Univ Alicante, Dept Comp Technol, E-03080 Alicante, Spain

[3] British Univ Egypt, Fac Informat & Comp Sci, Elsherouk City, Egypt

关键词: Medical shapes;    MRI;    3D surface reconstruction;    Landmarking;    Growing neural gas;    Voxel Grid;   

DOI  :  10.1016/j.neucom.2014.03.078

来源: Elsevier

【 摘 要 】

In this study, we utilise a novel approach to segment out the ventricular system in a series of high resolution Ti-weighted MR images. We present a brain ventricles fast reconstruction method. The method is based on the processing of brain sections and establishing a fixed number of landmarks onto those sections to reconstruct the ventricles 3D surface. Automated landmark extraction is accomplished through the use of the self-organising network, the growing neural gas (GNG), which is able to topographically map the low dimensionality of the network to the high dimensionality of the contour manifold without requiring a priori knowledge of the input space structure. Moreover, our GNG landmark method is tolerant to noise and eliminates outliers. Our method accelerates the classical surface reconstruction and filtering processes. The proposed method offers higher accuracy compared to methods with similar efficiency as Voxel Grid. (C) 2014 Elsevier B.V. All rights reserved.

【 授权许可】

Free