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Two-stage neural network for volume segmentation of medical images

Mohamed N. Ahmed, Aly A. Farag
1997 Pattern Recognition Letters  
We demonstrate the power of this approach to volume segmentation of medical images. q 1997 Elsevier Science B.V.  ...  The first stage is a self-organizing principal components analysis SOPCA network that is used to project the feature vector onto its leading principal axes found by using principal components analysis.  ...  Ž . 1983 and Koenderink 1984 as the image representation for multiscale analysis. A linked set of image replicas has been called a stack for 2D images, and a hyperstack for 3D images.  ... 
doi:10.1016/s0167-8655(97)00091-3 fatcat:qjmb2duwaja4vnefjkclurq2nu

Multi-phase Three-Dimensional Level Set Segmentation of Brain MRI [chapter]

Elsa D. Angelini, Ting Song, Brett D. Mensh, Andrew Laine
2004 Lecture Notes in Computer Science  
on brain T1 MRI images.  ...  The segmentation method was tested on ten MRI brain data sets and quantitative evaluation was performed by comparison to manually labeled data, Computation of false positive and false negative assignments  ...  [11] , a 'hyperstack' segmentation method, based on multiscale pixel classification, was tested for 3D brain MRI segmentation.  ... 
doi:10.1007/978-3-540-30135-6_39 fatcat:omcx7tqtyrgjxelsoyuoohuc5y

Segmentation and quantitative evaluation of brain MRI data with a multiphase 3D implicit deformable model

Elsa D. Angelini, Ting Song, Brett D. Mensh, Andrew Laine, J. Michael Fitzpatrick, Milan Sonka
2004 Medical Imaging 2004: Image Processing  
This random initialization ensures robustness of the method to variation of user expertise, biased a priori information and errors in input information that could be influenced by variations in image quality  ...  Segmentation of three-dimensional anatomical brain images into tissue classes has applications in both clinical and research settings.  ...  In Niessen et al. 13 , a 'hyperstack' segmentation method, based on multiscale pixel classification, was tested for 3D brain MRI segmentation.  ... 
doi:10.1117/12.535860 dblp:conf/miip/AngeliniSML04 fatcat:zaeuzeutqzclvdh6bkwprj4ryi

Brain MRI Segmentation with Multiphase Minimal Partitioning: A Comparative Study

Elsa D. Angelini, Ting Song, Brett D. Mensh, Andrew F. Laine
2007 International Journal of Biomedical Imaging  
Postprocessing corrections with morphological operators were applied to refine the details of the global segmentation method.  ...  The segmentation algorithm performs an optimal partitioning of three-dimensional data based on homogeneity measures that naturally evolves to the extraction of different tissue types in the brain.  ...  [55] , a "hyperstack" segmentation method, based on multiscale pixel classification, was tested for 3D brain MRI segmentation.  ... 
doi:10.1155/2007/10526 pmid:18253474 pmcid:PMC2211521 fatcat:5hok2fmenraffotpvvrgcd6wp4

Transitions of a Multi-scale Image Hierarchy Tree [chapter]

Arjan Kuijper
2009 Lecture Notes in Computer Science  
We investigate the deep structure of a scale space image. We concentrate on scale space critical pointspoints with vanishing gradient with respect to both spatial and scale direction.  ...  They turn out to be extremely useful, since the iso-intensity manifolds through these points provide a scale space hierarchy tree and induce a "pre-segmentation": a segmentation without a priori knowledge  ...  Since the Fig. 14(b) and (c) are probabilistic segmentations, they are made binary by thresholding them on the value 128.  ... 
doi:10.1007/978-3-642-02256-2_70 fatcat:skl4fkxgjvcl5jcqbq57yl4jyy