1.
Zagal, Juan Cristobal, et al.
(author)
Signficance determination for the scale-space primal sketch by comparison of statistics of scale-space blob volumes computed from PET signals vs. residual noise
2000
Conference paper (peer-reviewed) abstract
A dominant approach to brain mapping is to define functional regions in the brain by analyzing brain activation images obtained by PET or fMRI. In [1], it has been shown that the scale-space primal sketch provides a useful tool for such analysis. Some attractive properties of this method are that it only makes few assumptions about the data and the process for extracting activations is fully automatic.In the present version of the scale-space primal sketch, however, there is no method for determining p-values. The purpose here is to present a new methodology for addressing this question, by introducing a descriptor referred to as the -curve, which serves as a first step towards determining the probability of false positives, i.e. alpha.
2.
Bretzner, Lars, et al.
(author)
Qualitative Multi-Scale Feature Hierarchies for Object Tracking
2000
In: Journal of Visual Communication and Image Representation. - : Elsevier. - 1047-3203 .- 1095-9076. ; 11, s. 115-129
Journal article (peer-reviewed) abstract
This paper shows how the performance of feature trackers can be improved by building a view-based object representation consisting of qualitative relations between image structures at different scales. The idea is to track all image features individually, and to use the qualitative feature relations for resolving ambiguous matches and for introducing feature hypotheses whenever image features are mismatched or lost. Compared to more traditional work on view-based object tracking, this methodology has the ability to handle semi-rigid objects and partial occlusions. Compared to trackers based on three-dimensional object models, this approach is much simpler and of a more generic nature. A hands-on example is presented showing how an integrated application system can be constructed from conceptually very simple operations.
3.
Björkman, Eva, et al.
(author)
Evaluation of design options for the scale-space primal sketch analysis of brain activation images
2000
Conference paper (peer-reviewed) abstract
A key issue in brain imaging concerns how to detect the functionally activated regions from PET and fMRI images. In earlier work, it has been shown that the scale-space primal sketch provides a useful tool for such analysis [1]. The method includes presmoothing with different filter widths and automatic estimation of the spatial extent of the activated regions (blobs).The purpose is to present two modifications of the scale-space primal sketch, as well as a quantitative evaluation which shows that these modifications improve the performance, measured as the separation between blob descriptors extracted from PET images and from noise images. This separation is essential for future work of associating a statistical p-value with the scale-space blob descriptors.
4.
Almansa, A., et al.
(author)
Fingerprint enhancement by shape adaptation of scale-space operators with automatic scale selection
2000
In: IEEE Transactions on Image Processing. - : IEEE Signal Processing Society. - 1057-7149 .- 1941-0042. ; 9:12, s. 2027-2042
Journal article (peer-reviewed) abstract
This work presents two mechanisms for processing fingerprint images; shape-adapted smoothing based on second moment descriptors and automatic scale selection based on normalized derivatives. The shape adaptation procedure adapts the smoothing operation to the local ridge structures, which allows interrupted ridges to be joined without destroying essential singularities such as branching points and enforces continuity of their directional fields. The Scale selection procedure estimates local ridge width and adapts the amount of smoothing to the local amount of noise. In addition, a ridgeness measure is defined, which reflects how well the local image structure agrees with a qualitative ridge model, and is used for spreading the results of shape adaptation into noisy areas. The combined approach makes it possible to resolve fine scale structures in clear areas while reducing the risk of enhancing noise in blurred or fragmented areas. The result is a reliable and adaptively detailed estimate of the ridge orientation field and ridge width, as well as a Smoothed grey-level version of the input image. We propose that these general techniques should be of interest to developers of automatic fingerprint identification systems as well as in other applications of processing related types of imagery.
5.
Laptev, Ivan, et al.
(author)
Automatic extraction of roads from aerial images based on scale space and snakes
2000
In: Machine Vision and Applications. - : Springer. - 0932-8092 .- 1432-1769. ; 12:1, s. 23-31
Journal article (peer-reviewed) abstract
We propose a new approach for automatic road extraction from aerial imagery with a model and a strategy mainly based on the multi-scale detection of roads in combination with geometry-constrained edge extraction using snakes. A main advantage of our approach is, that it allows for the first time a bridging of shadows and partially occluded areas using the heavily disturbed evidence in the image. Additionally, it has only few parameters to be adjusted. The road network is constructed after extracting crossings with varying shape and topology. We show the feasibility of the approach not only by presenting reasonable results but also by evaluating them quantitatively based on ground truth.
6.
Gärdenfors, Peter, et al.
(author)
The origin of symbols in the brain
2000
In: Paper presented at the conference on Evolution of Language, March 6-9, 2000, Paris.
Conference paper (peer-reviewed)
7.
Thurfjell, L, et al.
(author)
Improved efficiency for MRI-SPET registration based on mutual information
2000
In: EUROPEAN JOURNAL OF NUCLEAR MEDICINE. - 0340-6997. ; 27:7, s. 847-856
Journal article (peer-reviewed) abstract
Mutual information has been proposed as a criterion for image registration. The criterion is calculated from a two-dimensional grey-scale histogram of the image pair being registered, In this paper we study how sparse sampling can be used to increase spee
8.
Barnden, L, et al.
(author)
Validation of fully automatic brain SPET to MR co-registration
2000
In: EUROPEAN JOURNAL OF NUCLEAR MEDICINE. - 0340-6997. ; 27:2, s. 147-154
Journal article (peer-reviewed) abstract
Fully automatic co-registration of functional to anatomical brain images using information intrinsic to the scans has been validated in a clinical setting for positron emission tomography (PET), but not for single-photon emission tomography (SPET). In thi
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