| 1. |
- Roland, P, et al.
(författare)
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A database generator for human brain imaging
- 2001
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Ingår i: TINS - Trends in Neurosciences. - 0166-2236 .- 1878-108X. ; 24:10, s. 562-564
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Tidskriftsartikel (refereegranskat)abstract
- Sharing scientific data containing complex information requires new concepts and new technology. NEUROGENERATOR is a database generator for the neuroimaging community. A database generator is a database that generates new databases. The scientists submit raw PET and fMRI data to NEUROGENERATOR, which then processes the data in a uniform way to create databases of homogenous data suitable for data sharing, met-analysis and modelling the human brain at the systems level. These databases are then distributed to the scientists.
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| 2. |
- Rosbacke, M., et al.
(författare)
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Evaluation of using absolute versus relative base level when analyzing brain activation images using the scale-space primal sketch
- 2001
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Ingår i: Medical Image Analysis. - 1361-8415 .- 1361-8423. ; 5:2, s. 89-110
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Tidskriftsartikel (refereegranskat)abstract
- A dominant approach to brain mapping is to define functional regions in the brain by analyzing images of brain activation obtained from positron emission tomography (PET) and functional magnetic resonance imaging (fMRI). This paper presents an evaluation of using one such tool, called the scale-space primal sketch, for brain activation analysis. A comparison is made concerning two possible definitions of a significance measure of blob structures in scale-space, where local contrast is measured either relative to a local or global reference level. Experiments on real brain data show that (i) the global approach with absolute base level has a higher degree of correspondence to a traditional statistical method than a local approach with relative base level, and that (ii) the global approach with absolute base level gives a higher significance to small blobs that are superimposed on larger scale structures, whereas the significance of isolated blobs largely remains unaffected. Relative to previously reported works, the following two technical improvements are also presented. (i) A post-processing tool is introduced for merging blobs that are multiple responses to image structures. This simplifies automated analysis from the scale-space primal sketch. (ii) A new approach is introduced for scale-space normalization of the significance measure, by collecting reference statistics of residual noise images obtained from the general Linear model.
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| 3. |
- Zagal, Juan Cristobal, et al.
(författare)
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Signficance determination for the scale-space primal sketch by comparison of statistics of scale-space blob volumes computed from PET signals vs. residual noise
- 2000
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Konferensbidrag (refereegranskat)abstract
- A dominant approach to brain mapping is to define functional regions in the brain by analyzing brain activation images obtained by PET or fMRI. In [1], it has been shown that the scale-space primal sketch provides a useful tool for such analysis. Some attractive properties of this method are that it only makes few assumptions about the data and the process for extracting activations is fully automatic.In the present version of the scale-space primal sketch, however, there is no method for determining p-values. The purpose here is to present a new methodology for addressing this question, by introducing a descriptor referred to as the -curve, which serves as a first step towards determining the probability of false positives, i.e. alpha.
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| 4. |
- Dahl, Ingolf, 1950
(författare)
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How to measure the Mueller matrix of liquid-crystal cells
- 2001
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Ingår i: Meas. Sci. Technol.. - 0957-0233. ; 12, s. 1938-1948
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Tidskriftsartikel (refereegranskat)abstract
- The Mueller matrix is the transfer matrix in the Stokes algebra that describes the polarization of natural light. This matrix is very versatile for the task of characterizing the optical properties of liquid-crystal cells, since it can be used for comparison with theoretical calculations, the determination of material parameters and the modelling of the cell as an optical building block for technological use. We have constructed a Mueller-matrix spectrometer, with the ability to perform fast, dynamic measurements of the Mueller matrix of small areas of liquid-crystal cells throughout the visible range. To illustrate the potential of the instrument, dynamic measurements on a ferroelectric-liquid-crystal cell are presented and analysed. The optical measurements indicate that there is an asymmetry between the up and the down state, tilted smectic layers and polarization reversal initiated at the boundaries.
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| 8. |
- Laptev, Ivan, et al.
(författare)
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A distance measure and a feature likelihood map concept for scale-invariant model matching
- 2003
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Ingår i: International Journal of Computer Vision. - : Kluwer Academic Publishers. - 0920-5691 .- 1573-1405. ; 52:2, s. 97-120
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Rapport (refereegranskat)abstract
- This paper presents two approaches for evaluating multi-scale feature-based object models. Within the first approach, a scale-invariant distance measure is proposed for comparing two image representations in terms of multi-scale features. Based on this measure, the maximisation of the likelihood of parameterised feature models allows for simultaneous model selection and parameter estimation. The idea of the second approach is to avoid an explicit feature extraction step and to evaluate models using a function defined directly from the image data. For this purpose, we propose the concept of a feature likelihood map, which is a function normalised to the interval [0, 1], and that approximates the likelihood of image features at all points in scale-space. To illustrate the applicability of both methods, we consider the area of hand gesture analysis and show how the proposed evaluation schemes can be integrated within a particle filtering approach for performing simultaneous tracking and recognition of hand models under variations in the position, orientation, size and posture of the hand. The experiments demonstrate the feasibility of the approach, and that real time performance can be obtained by pyramid implementations of the proposed concepts.
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| 9. |
- Laptev, Ivan, et al.
(författare)
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Tracking of multi-state hand models using particle filtering and a hierarchy of multi-scale image features
- 2001
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Ingår i: Scale-Space and Morphology in Computer Vision. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 3540423176 ; , s. 63-74
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Konferensbidrag (refereegranskat)abstract
- This paper presents an approach for simultaneous tracking and recognition of hierarchical object representations in terms of multiscale image features. A scale-invariant dissimilarity measure is proposed for comparing scale-space features at different positions and scales. Based on this measure, the likelihood of hierarchical, parameterized models can be evaluated in such a way that maximization of the measure over different models and their parameters allows for both model selection and parameter estimation. Then, within the framework of particle filtering, we consider the area of hand gesture analysis, and present a method for simultaneous tracking and recognition of hand models under variations in the position, orientation, size and posture of the hand. In this way, qualitative hand states and quantitative hand motions can be captured, and be used for controlling different types of computerised equipment.
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| 10. |
- Smeraldi, Fabrizio, et al.
(författare)
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Support vector features and the role of dimensionality in face authentication
- 2002
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Ingår i: Pattern recognition with support vector machines. - Heidelberg : Springer Berlin/Heidelberg. - 9783540440161 - 9783540456650 ; , s. 249-259
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- A study of the dimensionality of the Face Authentication problem using Principal Component Analysis (PCA) and a novel dimensionality reduction algorithm that we call Support Vector Features (SVFs) is presented. Starting from a Gabor feature space, we show that PCA and SVFs identify distinct subspaces with comparable authentication and generalisation performance. Experiments using KNN classifiers and Support Vector Machines (SVMs) on these reduced feature spaces show that the dimensionality at which saturation of the authentication performance is achieved heavily depends on the choice of the classifier. In particular, SVMs involve directions in feature space that carry little variance and therefore appear to be vulnerable to excessive PCA-based compression. © Springer-Verlag Berlin Heidelberg 2002.
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