| 1. |
- Andersson, Erik, 1966, et al.
(författare)
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Power and security
- 1999
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Ingår i: Schulz, M. (ed.), Peace and development - their interrelationship in the global system: an inventory of peace and development research at PADRIGU: a Festschrift in honour of professor Björn Hettne. - Göteborg : Padrigu Papers, Göteborgs universitet. - 9187380447
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Bokkapitel (övrigt vetenskapligt/konstnärligt)
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| 2. |
- Andersson, Thord, et al.
(författare)
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A Fast Optimization Method for Level Set Segmentation
- 2009
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Ingår i: Image Analysis. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783642022296 - 9783642022302 ; , s. 400-409
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Konferensbidrag (refereegranskat)abstract
- Level set methods are a popular way to solve the image segmentation problem in computer image analysis. A contour is implicitly represented by the zero level of a signed distance function, and evolved according to a motion equation in order to minimize a cost function. This function defines the objective of the segmentation problem and also includes regularization constraints. Gradient descent search is the de facto method used to solve this optimization problem. Basic gradient descent methods, however, are sensitive for local optima and often display slow convergence. Traditionally, the cost functions have been modified to avoid these problems. In this work, we instead propose using a modified gradient descent search based on resilient propagation (Rprop), a method commonly used in the machine learning community. Our results show faster convergence and less sensitivity to local optima, compared to traditional gradient descent.
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| 3. |
- Andersson, Thord, et al.
(författare)
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Consistent intensity inhomogeneity correction in water-fat MRI
- 2015
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Ingår i: Journal of Magnetic Resonance Imaging. - : Wiley-Blackwell. - 1053-1807 .- 1522-2586. ; 42:2
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Tidskriftsartikel (refereegranskat)abstract
- PURPOSE: To quantitatively and qualitatively evaluate the water-signal performance of the consistent intensity inhomogeneity correction (CIIC) method to correct for intensity inhomogeneitiesMETHODS: Water-fat volumes were acquired using 1.5 Tesla (T) and 3.0T symmetrically sampled 2-point Dixon three-dimensional MRI. Two datasets: (i) 10 muscle tissue regions of interest (ROIs) from 10 subjects acquired with both 1.5T and 3.0T whole-body MRI. (ii) Seven liver tissue ROIs from 36 patients imaged using 1.5T MRI at six time points after Gd-EOB-DTPA injection. The performance of CIIC was evaluated quantitatively by analyzing its impact on the dispersion and bias of the water image ROI intensities, and qualitatively using side-by-side image comparisons.RESULTS: CIIC significantly ( P1.5T≤2.3×10-4,P3.0T≤1.0×10-6) decreased the nonphysiological intensity variance while preserving the average intensity levels. The side-by-side comparisons showed improved intensity consistency ( Pint≤10-6) while not introducing artifacts ( Part=0.024) nor changed appearances ( Papp≤10-6).CONCLUSION: CIIC improves the spatiotemporal intensity consistency in regions of a homogenous tissue type.
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| 4. |
- Andersson, Thord, 1972-, et al.
(författare)
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Fuzzy matching of visual cues in an unmanned airborne vehicle
- 1999
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Computer vision systems used in autonomous mobile vehicles are typically linked to higher-level deliberation processes. One important aspect of this link is how to connect, or anchor, the symbols used at the higher level to the objects in the vision system that these symbols refer to. Anchoring is complicated by the fact that the vision data are inherently affected by uncertainty. We propose an anchoring technique that uses fuzzy sets to represent the uncertainty in the perceptual data. We show examples where this technique allows a deliberative system to reason about the objects (cars) detected by a vision system embarked in an unmanned helicopter, in the framework of the Witas project.
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| 5. |
- Andersson, Thord, 1972-, et al.
(författare)
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Geodesic registration for interactive atlas-based segmentation using learned multi-scale anatomical manifolds
- 2018
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Ingår i: Pattern Recognition Letters. - : Elsevier. - 0167-8655 .- 1872-7344. ; 112, s. 340-345
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Tidskriftsartikel (refereegranskat)abstract
- Atlas-based segmentation is often used to segment medical image regions. For intensity-normalized data, the quality of these segmentations is highly dependent on the similarity between the atlas and the target under the used registration method. We propose a geodesic registration method for interactive atlas-based segmentation using empirical multi-scale anatomical manifolds. The method utilizes unlabeled images together with the labeled atlases to learn empirical anatomical manifolds. These manifolds are defined on distinct scales and regions and are used to propagate the labeling information from the atlases to the target along anatomical geodesics. The resulting competing segmentations from the different manifolds are then ranked according to an image-based similarity measure. We used image volumes acquired using magnetic resonance imaging from 36 subjects. The performance of the method was evaluated using a liver segmentation task. The result was then compared to the corresponding performance of direct segmentation using Dice Index statistics. The method shows a significant improvement in liver segmentation performance between the proposed method and direct segmentation. Furthermore, the standard deviation in performance decreased significantly. Using competing complementary manifolds defined over a hierarchy of region of interests gives an additional improvement in segmentation performance compared to the single manifold segmentation.
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| 6. |
- Andersson, Thord
(författare)
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Learning in a Reactive Robotic Architecture
- 2000
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In this licenciate thesis, we discuss how to generate actions from percepts within an autonomous robotic system. In particular, we discuss and propose an original reactive architecture suitable for response generation, learning and self-organization.The architecture uses incremental learning and supports self organization through distributed dynamic model generation and self-contained components. Signals to and from the architecture are represented using the channel representation, which is presented in that context.The components of the architecture use a novel and flexible implementation of an artificial neural network. The learning rules for this implementation are derived.A simulator is presented. It has been designed and implemented in order to test and evaluate the proposed architecture.Results of a series of experiments on the reactive architecture are discussed and accounted for. The experiments have been performed within three different scenarios, using the developed simulator.The problem of information representation in robotic architectures is illustrated by a problem of anchoring symbols to visual data. This is presented in the context of the WITAS project.
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| 7. |
- Andersson, Thord, et al.
(författare)
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Modified Gradient Search for Level Set Based Image Segmentation
- 2013
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Ingår i: IEEE Transactions on Image Processing. - : IEEE Signal Processing Society. - 1057-7149 .- 1941-0042. ; 22:2, s. 621-630
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Tidskriftsartikel (refereegranskat)abstract
- Level set methods are a popular way to solve the image segmentation problem. The solution contour is found by solving an optimization problem where a cost functional is minimized. Gradient descent methods are often used to solve this optimization problem since they are very easy to implement and applicable to general nonconvex functionals. They are, however, sensitive to local minima and often display slow convergence. Traditionally, cost functionals have been modified to avoid these problems. In this paper, we instead propose using two modified gradient descent methods, one using a momentum term and one based on resilient propagation. These methods are commonly used in the machine learning community. In a series of 2-D/3-D-experiments using real and synthetic data with ground truth, the modifications are shown to reduce the sensitivity for local optima and to increase the convergence rate. The parameter sensitivity is also investigated. The proposed methods are very simple modifications of the basic method, and are directly compatible with any type of level set implementation. Downloadable reference code with examples is available online.
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| 8. |
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| 9. |
- Andersson, Thord, et al.
(författare)
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WITAS Project at Computer Vision Laboratory; A status report (Jan 1998)
- 1998
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Ingår i: Proceedings of the SSAB symposium on image analysis. ; , s. 113-116
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Konferensbidrag (refereegranskat)abstract
- WITAS will be engaged in goal-directed basic research in the area of intelligent autonomous vehicles and other autonomous systems. In this paper an overview of the project is given together with a presentation of our research interests in the project. The current status of our part in the project is also given.
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| 10. |
- Borga, Magnus, et al.
(författare)
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Semi-Supervised Learning of Anatomical Manifolds for Atlas-Based Segmentation of Medical Images
- 2016
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Ingår i: Proceedings of the 23rd International Conference on Pattern Recognition (ICPR). - : IEEE Computer Society. - 9781509048472 - 9781509048489 ; , s. 3146-3149
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Konferensbidrag (refereegranskat)abstract
- This paper presents a novel method for atlas-based segmentation of medical images. The method uses semi- supervised learning of a graph describing a manifold of anatom- ical variations of whole-body images, where unlabelled data are used to find a path with small deformations from the labelled atlas to the target image. The method is evaluated on 36 whole-body magnetic resonance images with manually segmented livers as ground truth. Significant improvement (p < 0.001) was obtained compared to direct atlas-based registration.
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