| 1. |
- Andersson, Kenneth, 1970-, et al.
(author)
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A perception based velocity estimator and its use for motion compensated prediction
- 2001
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In: SCIA 2001 Scandinavian Conference on Image Analysis,2001. ; , s. 493-499
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Conference paper (peer-reviewed)abstract
- The use of temporal redundancy is of vital importance for a successful video coding algorithm. An effective approach is the hybrid video coder where motion estimation is used for prediction of the next image frame and code the prediction error, and the motion field. The standard method for motion estimation is block matching as in MPEG-2, typically resulting in block artifacts. In this paper a perception based velocity estimator and its use for pixel based motion compensated prediction of interlaced video is presented.
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| 2. |
- Andersson, Kenneth, 1970-, et al.
(author)
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Backward-forward motion compensated prediction
- 2002
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In: Proceedings of ACIVS 2002 (Advanced Concepts for Intelligent Vision Systems), Ghent, Belgium, September 9-11, 2002. ; , s. 260-267
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Conference paper (peer-reviewed)abstract
- This paper presents new methods for use of dense motion fields for motion compensation of interlaced video. The motion is estimated using previously decoded field-images. An initial motion compensated prediction is produced using the assumption that the motion is predictable in time. The motion estimation algorithm is phase-based and uses two or three field-images to achieve motion estimates with sub-pixel accuracy. To handle non-constant motion and the specific characteristics of the field-image to be coded, the initially predicted image is refined using forward motion compensation, based on block-matching. Tests show that this approach achieves higher PSNR than forward block-based motion estimation, when coding the residual with the same coder. The subjective performance is also better.
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| 3. |
- Andersson, Kenneth, 1970-, et al.
(author)
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Continuous normalized convolution
- 2002
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In: Multimedia and Expo, 2002. ICME '02. Proceedings. 2002 IEEE International Conference on (Volume:1). - : IEEE. - 0780373049 ; , s. 725-728
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Conference paper (peer-reviewed)abstract
- The problem of signal estimation for sparsely and irregularly sampled signals is dealt with using continuous normalized convolution. Image values on real-valued positions are estimated using integration of signals and certainties over a neighbourhood employing a local model of both the signal and the used discrete filters. The result of the approach is that an output sample close to signals with high certainty is interpolated using a small neighbourhood. An output sample close to signals with low certainty is spatially predicted from signals in a large neighbourhood.
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| 4. |
- Andersson, Kenneth, 1970-, et al.
(author)
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Motion compensation using backward prediction and prediction refinement
- 2003
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In: Signal Processing: Image Communication. - 0923-5965. ; 18:5, s. 381-400
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Journal article (peer-reviewed)abstract
- This paper presents new methods for use of dense motion fields for motion compensation of interlaced video. The motion estimation is based on previously decoded field-images. The motion is then temporally predicted and used for motion compensated prediction of the field-image to be coded. The motion estimation algorithm is phase-based and uses two or three field-images to achieve motion estimates with sub-pixel accuracy. To handle non-constant motion and the specific characteristics of the field-image to be coded, the initially predicted image is refined using forward motion compensation, based on block-matching. Tests show that this approach achieves higher PSNR than forward block-based motion estimation, when coding the residual with the same coder. The subjective performance is also better.
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| 5. |
- Andersson, Kenneth, 1970-, et al.
(author)
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Multiple hierarchical motion estimation
- 2002
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In: Signal Processing, Pattern Recognition, and Applications - 2002. - : ACTA Press. ; , s. 80-
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Conference paper (peer-reviewed)abstract
- This paper introduce multiple hierarchical motion estimation to achieve motion estimates with high spatial resolution. The approach is based on phase-based motion estimation. Results show that the algorithm deal with the smooth motion field of hierarchical motion estimation while keeping the advantages of such an approach.
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| 6. |
- Andersson, Mats, 1960-, et al.
(author)
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Transformation of local spatio-temporal structure tensor fields
- 2003
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In: Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on (Volume:3 ). - : IEEE. - 0780376633 ; , s. 285-288
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Conference paper (peer-reviewed)abstract
- Tensors and tensor fields are commonly used in multidimensional signal processing to represent the local structure of the signal. This paper focuses on the case where the sampling on the original signal is anisotropic, e.g when the resolution of the multidimensional image varies depending on the direction which is common e.g. in medical imaging devices. To obtain a geometrically correct description of the local structure there are mainly two possibilities. To resample the image prior to the computation of the local structure tensor field or to compute the tensor field on the original grid and transform the result to obtain a correct geometry of the local structure. This paper deals with the latter alternative and contains an in depth theoretical analysis establishing the appropriate rules for tensor transformations induced by changes in space-time geometry with emphasis on velocity and motion estimation.
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| 7. |
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| 8. |
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| 9. |
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| 10. |
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| 11. |
- Brun, Anders, 1976-, et al.
(author)
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Clustering Fiber Traces Using Normalized Cuts
- 2004
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In: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2004. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783540229766 - 9783540301356 ; , s. 368-375
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Conference paper (peer-reviewed)abstract
- In this paper we present a framework for unsupervised segmentation of white matter fiber traces obtained from diffusion weighted MRI data. Fiber traces are compared pairwise to create a weighted undirected graph which is partitioned into coherent sets using the normalized cut (Ncut) criterion. A simple and yet effective method for pairwise comparison of fiber traces is presented which in combination with the Ncut criterion is shown to produce plausible segmentations of both synthetic and real fiber trace data. Segmentations are visualized as colored stream-tubes or transformed to a segmentation of voxel space, revealing structures in a way that looks promising for future explorative studies of diffusion weighted MRI data.
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| 12. |
- Brun, Anders, 1976-, et al.
(author)
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Coloring of DT-MRI fiber traces using Laplacian Eigenmaps
- 2003
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In: Computer Aided Systems Theory - EUROCAST 2003. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783540202219 - 9783540452102 ; , s. 518-529
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Conference paper (peer-reviewed)abstract
- We propose a novel post processing method for visualization of fiber traces from DT-MRI data. Using a recently proposed non-linear dimensionality reduction technique, Laplacian eigenmaps [3], we create a mapping from a set of fiber traces to a low dimensional Euclidean space. Laplacian eigenmaps constructs this mapping so that similar traces are mapped to similar points, given a custom made pairwise similarity measure for fiber traces. We demonstrate that when the low-dimensional space is the RGB color space, this can be used to visualize fiber traces in a way which enhances the perception of fiber bundles and connectivity in the human brain.
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| 13. |
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| 14. |
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| 15. |
- Friman, Ola, 1975-, et al.
(author)
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A Correlation Framwork For Functional Mri Data Analysis.
- 2001
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In: Proceedings of SCIA 2001. Bergen,2001. - 8299594006 ; , s. 3-9
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Conference paper (peer-reviewed)abstract
- A correlation framework for detecting brain activity in functional MRI data is presented. In this framework, a novel method based on canonical correlation analysis follows as a natural extension of established analysis methods. The new method shows very good detection performance. This is demonstrated by localizing brain areas which control finger movements and areas which are involved in numerical mental calculation.
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| 16. |
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| 17. |
- Friman, Ola, 1975-, et al.
(author)
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Detection of neural activity in functional MRI using canonical correlation analysis
- 2001
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In: Magnetic Resonance in Medicine. - 0740-3194 .- 1522-2594. ; 45:2, s. 323-330
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Journal article (peer-reviewed)abstract
- A novel method for detecting neural activity in functional magnetic resonance imaging (fMRI) data is introduced. It is based on canonical correlation analysis (CCA), which is a multivariate extension of the univariate correlation analysis widely used in fMRI. To detect homogeneous regions of activity, the method combines a subspace modeling of the hemodynamic response and the use of spatial relationships. The spatial correlation that undoubtedly exists in fMR images is completely ignored when univariate methods such as as t-tests, F-tests, and ordinary correlation analysis are used. Such methods are for this reason very sensitive to noise, leading to difficulties in detecting activation and significant contributions of false activations. In addition, the proposed CCA method also makes it possible to detect activated brain regions based not only on thresholding a correlation coefficient, but also on physiological parameters such as temporal shape and delay of the hemodynamic response. Excellent performance on real fMRI data is demonstrated.
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| 18. |
- Friman, Ola, 1975-, et al.
(author)
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Exploratory fMRI analysis by autocorrelation maximization
- 2002
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In: NeuroImage. - : Elsevier BV. - 1053-8119 .- 1095-9572. ; 16:2, s. 454-464
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Journal article (peer-reviewed)abstract
- A novel and computationally efficient method for exploratory analysis of functional MRI data is presented. The basic idea is to reveal underlying components in the fMRI data that have maximum autocorrelation. The tool for accomplishing this task is Canonical Correlation Analysis. The relation to Principal Component Analysis and Independent Component Analysis is discussed and the performance of the methods is compared using both simulated and real data.
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| 19. |
- Friman, Ola, 1975-, et al.
(author)
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Hierarchical temporal blind source separation of fMRI data
- 2002
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In: Proceedings of the ISMRM Annual Meeting (ISMRM'02).
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Conference paper (peer-reviewed)abstract
- Blind Source Separation (BSS) of fMRI data can be done both temporally and spatially. Temporal BSS of fMRI data has one fundamental problem not encountered in the spatial BSS approach. There are thousands of observed timecourses in an fMRI data set while the number of samples of each timecourse typically is less than two hundred. This re lation makes the problem of recovering the underlying temporal sources ill-posed. This contribution eliminates this problem by introducing a hierarchical approach for performing temporal BSS of fMRI data.
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| 20. |
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| 21. |
- Friman, Ola, 1975-, et al.
(author)
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Recognizing emphysema - A neural network approach
- 2002
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In: Pattern Recognition, 2002. Proceedings. 16th International Conference on (Volume:1). - : IEEE Computer Society. ; , s. 512-515
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Conference paper (peer-reviewed)abstract
- An accurate and fully automatic method for detecting and quantifying emphysema in CT-images is presented. The method is based on an image preprocessing step followed by a neural network classifier trained to separate true emphysema from artifacts. The proposed approach is shown to be superior to an established method when applied on real patient data.
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| 22. |
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| 23. |
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| 24. |
- Johansson, Björn, 1971-, et al.
(author)
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Detecting Rotational Symmetries using Normalized Convolution
- 2000
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In: Proceedings of the 15th International Conference on Pattern Recognition,2000. - : IEEE. - 0769507506 ; , s. 496-500 vol.3
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Conference paper (peer-reviewed)abstract
- Perceptual experiments indicate that corners and curvature are very important features in the process of recognition. This paper presents a new method to detect rotational symmetries, which describes complex curvature such as corners, circles, star, and spiral patterns. It works in two steps: 1) it extracts local orientation from a gray-scale or color image; and 2) it applies normalized convolution on the orientation image with rotational symmetry filters as basis functions. These symmetries can serve as feature points at a high abstraction level for use in hierarchical matching structures for 3D estimation, object recognition, image database retrieval, etc
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| 25. |
- Knutsson, Hans, 1950-, et al.
(author)
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Automated generation of representations in vision
- 2000
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In: International Conference on Pattern Recognition ICPR,2000. - Barcelona, Spain : IEEE. - 0769507506 ; , s. 59-66 vol.3
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Conference paper (peer-reviewed)abstract
- This paper presents a general strategy for automated generation of efficient representations in vision. The approach is highly task oriented and what constitutes the relevant information is defined by a set of examples. The examples are pairs of situations that are dependent through the chosen feature but are otherwise independent. Particularly important concepts in the work are mutual information and canonical correlation. How visual operators and representations can be generated from examples are presented for a number of features, e.g. local orientation, disparity and motion. Interesting similarities to biological vision functions are observed. The results clearly demonstrates the potential of combining advanced filtering techniques and learning strategies based on canonical correlation analysis (CCA).
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