Multilevel Spectral Partitioning for Efficient Image Segmentation and Tracking

Tolliver, David; Collins, Robert T.; Baker, Simon

doi:10.1109/acvmot.2005.83

Cited by 2 publications

(2 citation statements)

References 14 publications

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“…There is a growing literature on sparse GPPs for regression ( Lawrence, 2006; Quinonero-Candela and Rasmussen, 2005 ) used to formulate an approximate instead of a full GPP for use on large data-sets. Alternatively, multi-grid methods may be used ( Larin, 2004 ) or we can utilize the graphical structure of the model and apply graph-theoretic methods to optimally partition a graph into sub-graphs or nested graphs ( Tolliver et al, 2005 ). Recently, the computationally efficient properties of wavelets have been used to adaptively smooth fMRI parameter images ( Flandin and Penny, 2007 ).…”

Section: Discussionmentioning

confidence: 99%

Diffusion-based spatial priors for imaging

et al. 2007

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We describe a Bayesian scheme to analyze images, which uses spatial priors encoded by a diffusion kernel, based on a weighted graph Laplacian. This provides a general framework to formulate a spatial model, whose parameters can be optimized. The application we have in mind is a spatiotemporal model for imaging data. We illustrate the method on a random effects analysis of fMRI contrast images from multiple subjects; this simplifies exposition of the model and enables a clear description of its salient features. Typically, imaging data are smoothed using a fixed Gaussian kernel as a pre-processing step before applying a mass-univariate statistical model (e.g., a general linear model) to provide images of parameter estimates. An alternative is to include smoothness in a multivariate statistical model (Penny, W.D., Trujillo-Barreto, N.J., Friston, K.J., 2005. Bayesian fMRI time series analysis with spatial priors. Neuroimage 24, 350–362). The advantage of the latter is that each parameter field is smoothed automatically, according to a measure of uncertainty, given the data. In this work, we investigate the use of diffusion kernels to encode spatial correlations among parameter estimates. Nonlinear diffusion has a long history in image processing; in particular, flows that depend on local image geometry (Romeny, B.M.T., 1994. Geometry-driven Diffusion in Computer Vision. Kluwer Academic Publishers) can be used as adaptive filters. This can furnish a non-stationary smoothing process that preserves features, which would otherwise be lost with a fixed Gaussian kernel. We describe a Bayesian framework that incorporates non-stationary, adaptive smoothing into a generative model to extract spatial features in parameter estimates. Critically, this means adaptive smoothing becomes an integral part of estimation and inference. We illustrate the method using synthetic and real fMRI data.

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Section: Discussionmentioning

confidence: 99%

Diffusion-based spatial priors for imaging

et al. 2007

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“…18. The eighteen-year hiatus between Sure of You (1989) and Michael Tolliver Lives (2007) obviously creates a gap in this diachronic analysis of the language of AIDS in fiction. Such a gap proves difficult to bridge, since the development of the AIDS cocktail in 1996 virtually put an end to the publication of "AIDS fiction".…”

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A diachronic analysis of the language of AIDS in Armistead Maupin's Tales of the City

Klein-Scholz¹

2017

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Grâce aux Chroniques de San Francisco (Tales of the City), une saga en neuf volumes d’Armistead Maupin qui raconte en détail la vie d’un petit groupe de personnages vivant à San Francisco, cet article explore l’évolution diachronique du vocabulaire du SIDA. En premier lieu, il donne quelques éclairages sur le vocabulaire du SIDA et pose la question de sa nature spécialisée. Puis il examine plus précisément l’ “avant” et l’ “après,” la césure étant 1996, année où les thérapies antirétrovirales ont été mises au point et, partant, où le VIH/SIDA a changé de nature. Il montre que, dans l’ “avant,” les mots et les silences portent le poids de la mort et que, quand ce poids est levé, le langage reste pourtant marqué. La conclusion de cet article met en question les liens qui unissent les auteurs de “littérature du SIDA” et le domaine spécialisé, en utilisant l’idée développée par l’ancien directeur de l’ONUSIDA, Peter Piot, d’ “experts de l’expérience.”

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Multilevel Spectral Partitioning for Efficient Image Segmentation and Tracking

Abstract: Abstract

Cited by 2 publications

References 14 publications

Diffusion-based spatial priors for imaging

Diffusion-based spatial priors for imaging

A diachronic analysis of the language of AIDS in Armistead Maupin's Tales of the City

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