| 1. |
- Ohlsson, Henrik, 1981-, et al.
(författare)
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Enabling Bio-Feedback using Real-Time fMRI
- 2008
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Ingår i: 47th IEEE Conference on Decision and Control, 2008, CDC 2008. - Linköping : IEEE. - 9781424431236 ; , s. 3336-3341
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Konferensbidrag (refereegranskat)abstract
- Despite the enormous complexity of the human mind, fMRI techniques are able to partially observe the state of a brain in action. In this paper we describe an experimental setup for real-time fMRI in a bio-feedback loop. One of the main challenges in the project is to reach a detection speed, accuracy and spatial resolution necessary to attain sufficient bandwidth of communication to close the bio-feedback loop. To this end we have banked on our previous work on real-time filtering for fMRI and system identification, which has been tailored for use in the experiment setup. In the experiments presented the system is trained to estimate where a person in the MRI scanner is looking from signals derived from the visual cortex only. We have been able to demonstrate that the user can induce an action and perform simple tasks with her mind sensed using real-time fMRI. The technique may have several clinical applications, for instance to allow paralyzed and "locked in" people to communicate with the outside world. In the meanwhile, the need for improved fMRI performance and brain state detection poses a challenge to the signal processing community. We also expect that the setup will serve as an invaluable tool for neuro science research in general.
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| 2. |
- Rantakokko, Jouni, et al.
(författare)
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Accurate and Reliable Soldier and First Responder Indoor Positioning : Multi-Sensor Systems and Cooperative Localization
- 2011
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Ingår i: IEEE wireless communications. - : IEEE Communications Society. - 1536-1284 .- 1558-0687. ; 18:2, s. 10-18
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Tidskriftsartikel (refereegranskat)abstract
- A robust, accurate positioning system with seamless outdoor and indoor coverage is a highly needed tool for increasing safety in emergency response and military urban operations. It must be lightweight, small, inexpensive, and power efficient, and still provide meter-level accuracy during extended operations. GPS receivers, inertial sensors, and local radio-based ranging are natural choices for a multisensor positioning system. Inertial navigation with foot-mounted sensors is suitable as the core system in GPS denied environments, since it can yield meter-level accuracies for a few minutes. However, there is still a need for additional supporting sensors to keep the accuracy at acceptable levels during the duration of typical soldier and first responder operations. Suitable aiding sensors are three-axis magnetometers, barometers, imaging sensors, Doppler radars, and ultrasonic sensors. Furthermore, cooperative positioning, where first responders exchange position and error estimates in conjunction with performing radio-based ranging, is deemed a key technology. This article provides a survey on technologies and concepts for high accuracy soldier and first responder positioning systems, with an emphasis on indoor positioning.
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| 3. |
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| 4. |
- 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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| 5. |
- 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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| 6. |
- Rydell, Joakim, 1979-
(författare)
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Adaptive spatial filtering of fMRI data
- 2005
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Functional magnetic resonance imaging (tMRI) is a method for detecting brain regions that are activated when a certain task is carried out. The method is useful in planning of neurosurgical procedures, where knowledge of the exact locations of important functions is needed to avoid damage to these regions. It is also an important tool in neurological research, where it is used to investigate the function of the human brain.To find the activated regions, a sequence of images of the brain is collected while a patient or subject alters between resting and performing the task. The variations in image intensity over time is then compared to a model of the variations expected to be found in active parts of the brain. Locations where the intensity variations are similar to the model are considered to be activated by the task.Since the images are very noisy, filtering is needed before the detection of activation. 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 filtering of fMRI data. One of these is based on canonical correlation analysis (CCA), and is an extension of a previously proposed CCA-based method. As in the old method, CCA is used in each neighborhood to find a spatial fi lter that maximizes the correlation to the model of the intensity variation. A novel feature of the presented method is that it is rotationally invariant, i.e. that it is equally sensitivelo activated regions in different orientations.The other method is based on bilateral filtering. This method creates spatial filters which averages pixels with similar intensity variation. Since these filters are not optimized to maximize the similarity to the model of activated signals, the risk of declaring inactive pixels as active is lower compared to CCA-based methods.
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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, 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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| 9. |
- 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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| 10. |
- Rydell, Joakim, 1979-, et al.
(författare)
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Dimensionality and degrees of freedom in fMRI data analysis - a comparative study
- 2004
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Ingår i: Biomedical Imaging: Nano to Macro, 2004. IEEE International Symposium on. - : IEEE. - 0780383885 ; , s. 988-991 vol.1
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Konferensbidrag (refereegranskat)abstract
- Two- and three-dimensional isotropic and anisotropic spatial filters for adaptive fMRI data analysis are compared in terms of activation detection sensitivity and specificity. Evaluations using both real and artificial data are presented. It is shown that three-dimensional anisotropic filters provide superior activation detection performance.
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