| 1. |
- Borga, Magnus, et al.
(författare)
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Signal and Anatomical Constraints in Adaptive Filtering of fMRI Data
- 2007
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Ingår i: Biomedical Imaging: From Nano to Macro, 2007. ISBI 2007. - : IEEE. - 1424406722 ; , s. 432-435
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Konferensbidrag (refereegranskat)abstract
- An adaptive filtering method for fMRI data is presented. The method is related to bilateral filtering, but with a range filter that takes into account local similarities in signal as well as in anatomy. Performance is demonstrated on simulated and real data. It is shown that using both these similarity constraints give better performance than if only one of them is used, and clearly better than standard low-pass filtering.
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| 2. |
- Dahlqvist Leinhard, Olof, et al.
(författare)
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Quantification of abdominal fat accumulation during hyperalimentation using MRI
- 2009
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Ingår i: Proceedings of the ISMRM Annual Meeting (ISMRM'09), 2009. - Berkeley, CA, USA : International Society for Magnetic Resonance in Medicine. ; , s. 206-
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- There is an increasing demand for imaging methods that can be used for automatic, accurate and quantitative determination of the amounts of abdominal fat. Such methods are important as they will allow the evaluation of some of the risk factors underlying the ’metabolic syndrome’. The metabolic syndrome is becoming common in large parts of the world, and it appears that a dominant risk factor for developing this syndrome is abdominal obesity. Subjects that are afflicted with the metabolic syndrome are exposed to a high risk for developing a large range of diseases such as type 2 diabetes, cardiac failure, and stroke. The aim of this work
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| 3. |
- Leinhard, Olof Dahlqvist, et al.
(författare)
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Quantitative Abdominal Fat Estimation Using MRI
- 2008
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Ingår i: Proceedings - International Conference on Pattern Recognition. - : IEEE Computer Society. - 9781424421749 - 9781424421756 ; , s. 1-4
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Konferensbidrag (refereegranskat)abstract
- This paper introduces a new method for automaticquantification of subcutaneous, visceral and nonvisceralinternal fat from MR-images acquired usingthe two point Dixon technique in the abdominal region.The method includes (1) a three dimensionalphase unwrapping to provide water and fat images, (2)an image intensity inhomogeneity correction, and (3) amorphon based registration and segmentation of thetissue. This is followed by an integration of the correctedfat images within the different fat compartmentsthat avoids the partial volume effects associated withtraditional fat segmentation methods. The method wastested on 18 subjects before and after a period of fastfoodhyper-alimentation showing high stability andperformance in all analysis steps.
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| 4. |
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| 5. |
- Rydell, Joakim, 1979-, et al.
(författare)
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Adaptive filtering of fMRI data based on correlation and BOLD response similarity
- 2006
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Ingår i: Acoustics, Speech and Signal Processing, 2006. ICASSP 2006. Vol. 2. - : IEEE conference proceedings. - 142440469X ; , s. II-997-II-1000
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Konferensbidrag (refereegranskat)abstract
- In analysis of fMRI data, it is common to average neighboring voxels in order to obtain robust estimates of the correlations between voxel time-series and the model of the signal expected to be present in activated regions. We have previously proposed a method where only voxels with similar correlation coefficients are averaged. In this paper we extend this idea, and present a novel method for analysis of fMRI data. In the proposed method, only voxels with similar correlation coefficients and similar time-series are averaged. The proposed method is compared to our previous method and to two well-known filtering strategies, and is shown to have superior ability to discriminate between active and inactive voxels
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| 6. |
- Rydell, Joakim, 1979-, et al.
(författare)
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Adaptive fMRI data filtering based in tissue and signal similarities
- 2007
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Ingår i: Joint Annual Meeting ISMRM-ESMRMB,2007.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- A novel method for analyzing fMRI data is presented. In order to detect activation with the highest possible accuracy, adaptive filtering is used to enahancethe signal to noise ratio. Using a method similar to bilateral filtering, signals from different voxels are averaged if the voxels belong to the same type oftissue and their signal variations over time are similar. The detection performance is evaluated on synthetic and real data, and it is shown that the twocriterions for averaging complement each other, providing very good detection of activation.
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| 7. |
- Rydell, Joakim, 1979-
(författare)
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Advanced MRI Data Processing
- 2007
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Magnetic resonance imaging (MRI) is a very versatile imaging modality which can be used to acquire several different types of images. Some examples include anatomical images, images showing local brain activation and images depicting different types of pathologies. Brain activation is detected by means of functional magnetic resonance imaging (fMRI). This is useful e.g. in planning of neurosurgical procedures and in neurological research. To find the activated regions, a sequence of images of the brain is collected while a patient or subject alters between resting and performing a task. The variations in image intensity over time are then compared to a model of the variations expected to be found in active parts of the brain. Locations with high correlation between the intensity variations and the model are considered to be activated by the task.Since the images are very noisy, spatial filtering is needed before the activation can be detected. If adaptive filtering is used, i.e. if the filter at each location is adapted to the local neighborhood, very good detection performance can be obtained. This thesis presents two methods for adaptive spatial filtering of fMRI data. One of these is a modification of a previously proposed method, which at each position maximizes the similarity between the filter response and the model. A novel feature of the presented method is rotational invariance, i.e. equal sensitivity to activated regions in different orientations. The other method is based on bilateral filtering. At each position, this method averages pixels which are located in the same type of brain tissue and have similar intensity variation over time.A method for robust correlation estimation is also presented. This method automatically detects local bursts of noise in a signal and disregards the corresponding signal segments when the correlation is estimated. Hence, the correlation estimate is not affected by the noise bursts. This method is useful not only in analysis of fMRI data, but also in other applications where correlation is used to determine the similarity between signals.Finally, a method for correcting artifacts in complex MR images is presented. Complex images are used e.g. in the Dixon technique for separate imaging of water and fat. The phase of these images is often affected by artifacts and therefore need correction before the actual water and fat images can be calculated. The presented method for phase correction is based on an image integration technique known as the inverse gradient. The method is shown to provide good results even when applied to images with severe artifacts.
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| 8. |
- Rydell, Joakim, et al.
(författare)
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Bilateral Filtering of fMRI Data
- 2008
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Ingår i: IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING. - 1932-4553. ; 2:6, s. 891-896
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Tidskriftsartikel (refereegranskat)abstract
- We present a class of adaptive filtering techniques of functional magnetic resonance imaging (fMRI) data related to bilateral filtering. This class of methods average activities in consistent regions rather than regions that maximize correlation with a BOLD model. Similarity measures based on signal similarity and anatomical similarity are discussed and compared experimentally to standard linear low pass filtering. It is demonstrated that adaptive filtering provides improved detection of activated regions.
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| 9. |
- Rydell, Joakim, 1979-, et al.
(författare)
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Correlation controlled adaptive filtering for FMRI data
- 2005
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Ingår i: IFMBE Proceedings: NBC'05 13th Nordic Baltic Conference Biomedical Engineering and Medical Physics. - Umeå : IFMBE. ; , s. 193-194
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Konferensbidrag (refereegranskat)abstract
- In analysis of fMRI data, it is common to average neighboring voxels in order to obtain robust estimates of the correlations between voxel timeseries and the model of the signal expected to be present in activated regions. This paper presents a novel method for analysis of fMRI data, which extends this approach by averaging only neighboring voxels whose timeseries have similar correlation coefficients. A comparison between the new method and two other filtering strategies is also presented, and the novel method is shown to have superior ability to discriminate between active and inactive voxels.
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| 10. |
- Rydell, Joakim, 1979-, et al.
(författare)
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Correlation controlled bilateral filtering of fMRI data
- 2005
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Ingår i: Proceedings of the International Society for Magnetic Resonance in MEdicine Annual Meeting (ISMRM) 2005.
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Konferensbidrag (refereegranskat)abstract
- A novel filtering method for analysis of fMRI data is presented. The method is based on weighted averaging of neighboring voxels whose time-series are, in a sense, similar. A comparison between the new method and other filtering strategies is also presented, and the novel method is shown to have superior ability to discriminate between active and inactive voxels.
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