| 1. |
- Abramian, David, 1992-, et al.
(författare)
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Anatomically Informed Bayesian Spatial Priors for FMRI Analysis
- 2020
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Ingår i: ISBI 2020. - : IEEE. - 9781538693308
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Konferensbidrag (refereegranskat)abstract
- Existing Bayesian spatial priors for functional magnetic resonance imaging (fMRI) data correspond to stationary isotropic smoothing filters that may oversmooth at anatomical boundaries. We propose two anatomically informed Bayesian spatial models for fMRI data with local smoothing in each voxel based on a tensor field estimated from a T1-weighted anatomical image. We show that our anatomically informed Bayesian spatial models results in posterior probability maps that follow the anatomical structure.
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| 2. |
- Afzali, Maryam, et al.
(författare)
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Computing the orientational-average of diffusion-weighted MRI signals : a comparison of different techniques
- 2021
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Ingår i: Scientific Reports. - : Nature Research. - 2045-2322. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- Numerous applications in diffusion MRI involve computing the orientationally-averaged diffusion-weighted signal. Most approaches implicitly assume, for a given b-value, that the gradient sampling vectors are uniformly distributed on a sphere (or shell), computing the orientationally-averaged signal through simple arithmetic averaging. One challenge with this approach is that not all acquisition schemes have gradient sampling vectors distributed over perfect spheres. To ameliorate this challenge, alternative averaging methods include: weighted signal averaging; spherical harmonic representation of the signal in each shell; and using Mean Apparent Propagator MRI (MAP-MRI) to derive a three-dimensional signal representation and estimate its isotropic part. Here, these different methods are simulated and compared under different signal-to-noise (SNR) realizations. With sufficiently dense sampling points (61 orientations per shell), and isotropically-distributed sampling vectors, all averaging methods give comparable results, (MAP-MRI-based estimates give slightly higher accuracy, albeit with slightly elevated bias as b-value increases). As the SNR and number of data points per shell are reduced, MAP-MRI-based approaches give significantly higher accuracy compared with the other methods. We also apply these approaches to in vivo data where the results are broadly consistent with our simulations. A statistical analysis of the simulated data shows that the orientationally-averaged signals at each b-value are largely Gaussian distributed.
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| 3. |
- Andersson, Kenneth, 1970-, et al.
(författare)
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A perception based velocity estimator and its use for motion compensated prediction
- 2001
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Ingår i: SCIA 2001 Scandinavian Conference on Image Analysis,2001. ; , s. 493-499
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Konferensbidrag (refereegranskat)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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| 4. |
- Andersson, Kenneth, 1970-, et al.
(författare)
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Backward-forward motion compensated prediction
- 2002
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Ingår i: Proceedings of ACIVS 2002 (Advanced Concepts for Intelligent Vision Systems), Ghent, Belgium, September 9-11, 2002. ; , s. 260-267
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Konferensbidrag (refereegranskat)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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| 5. |
- Andersson, Kenneth, 1970-, et al.
(författare)
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Continuous normalized convolution
- 2002
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Ingår i: Multimedia and Expo, 2002. ICME '02. Proceedings. 2002 IEEE International Conference on (Volume:1). - : IEEE. - 0780373049 ; , s. 725-728
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Konferensbidrag (refereegranskat)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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| 6. |
- Andersson, Kenneth, 1970-, et al.
(författare)
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Motion compensation using backward prediction and prediction refinement
- 2003
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Ingår i: Signal Processing: Image Communication. - 0923-5965. ; 18:5, s. 381-400
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Tidskriftsartikel (refereegranskat)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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| 7. |
- Andersson, Kenneth, 1970-, et al.
(författare)
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Multiple hierarchical motion estimation
- 2002
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Ingår i: Signal Processing, Pattern Recognition, and Applications - 2002. - : ACTA Press. ; , s. 80-
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Konferensbidrag (refereegranskat)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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| 8. |
- Andersson, Kenneth, 1970-, et al.
(författare)
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Prediction from off-grid samples using continuous normalized convolution
- 2007
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 87:3, s. 353-365
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents a novel method for performing fast estimation of data samples on a desired output grid from samples on an irregularly sampled grid. The output signal is estimated using integration of signals over a neighbourhood employing a local model of the signal using discrete filters. The strength of the method is demonstrated in motion compensation examples by comparing to traditional techniques.
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| 9. |
- Andersson, Mats, et al.
(författare)
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Adaptiv filtering of 4D-heart CT for image denoising and patient safety
- 2010
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- The aim of this medical image science project is to increase patient safety in terms of improved image quality and reduced exposure to ionizing radiation in CT. The means to achieve these goals is to develop and evaluate an efficient adaptive filtering (denoising/image enhancement) method that fully explores true 4D image acquisition modes. Four-dimensional (4D) medical image data are captured as a time sequence of image volumes. During 4D image acquisition, a 3D image of the patient is recorded at regular time intervals. The resulting data will consequently have three spatial dimensions and one temporal dimension. Increasing the dimensionality of the data impose a major increase the computational demands. The initial linear filtering which is the cornerstone in all adaptive image enhancement algorithms increase exponentially with the dimensionality. On the other hand the potential gain in Signal to Noise Ratio (SNR) also increase exponentially with the dimensionality. This means that the same gain in noise reduction that can be attained by performing the adaptive filtering in 3D as opposed to 2D can be expected to occur once more by moving from 3D to 4D. The initial tests on on both synthetic and clinical 4D images has resulted in a significant reduction of the noise level and an increased detail compared to 2D and 3D methods. When tuning the parameters for adaptive filtering is extremely important to attain maximal diagnostic value which not necessarily coincide with an an eye pleasing image for a layman. Although this application focus on CT the resulting adaptive filtering methods will be beneficial for a wide range of 3D/4D medical imaging modalities e.g. shorter acquisition time in MRI and improved elimination of noise in 3D or 4D ultrasound datasets.
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| 10. |
- Andersson, Mats, et al.
(författare)
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Adaptive Spatio-temporal Filtering of 4D CT-Heart
- 2013
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Ingår i: Image Analyses. - Berlin Heidelberg : Springer. - 9783642388859 - 9783642388866 ; , s. 246-255
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Konferensbidrag (refereegranskat)abstract
- The aim of this project is to keep the x-ray exposure of the patient as low as reasonably achievable while improving the diagnostic image quality for the radiologist. The means to achieve these goals is to develop and evaluate an efficient adaptive filtering (denoising/image enhancement) method that fully explores true 4D image acquisition modes.The proposed prototype system uses a novel filter set having directional filter responses being monomials. The monomial filter concept is used both for estimation of local structure and for the anisotropic adaptive filtering. Initial tests on clinical 4D CT-heart data with ECG-gated exposure has resulted in a significant reduction of the noise level and an increased detail compared to 2D and 3D methods. Another promising feature is that the reconstruction induced streak artifacts which generally occur in low dose CT are remarkably reduced in 4D.
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