Sune Darkner

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Statistical region-based registration methods such as the active appearance model (AAM) are used for establishing dense correspondences in images. At low resolution, images correspondences can be recovered reliably in real-time. However, as resolution increases this becomes infeasible due to excessive storage and computational requirements. We propose to(More)
Differentiation of the minimally conscious state (MCS) and the unresponsive wakefulness syndrome (UWS) is a persistent clinical challenge [1]. Based on positron emission tomography (PET) studies with [(18)F]-fluorodeoxyglucose (FDG) during sleep and anesthesia, the global cerebral metabolic rate of glucose has been proposed as an indicator of consciousness(More)
We propose a method for estimating the thickness of ultra thin histological sections by image statistics alone. Our method works for images, that are realisations of a stationary and isotropic stochastic process, and it relies on the existence of statistical image-measures that are strictly monotonic with distance. We propose to use the standard deviation(More)
Face recognition systems are typically required to work under highly varying illumination conditions. This leads to complex effects imposed on the acquired face image that pertains little to the actual identity. Consequently, illumination normalization is required to reach acceptable recognition rates in face recognition systems. In this paper, we propose(More)
This paper presents a unifying approach for calculating a wide range of popular, but seemingly very different, similarity measures. Our domain is the registration of n-dimensional images sampled on a regular grid, and our approach is well suited for gradient-based optimization algorithms. Our approach is based on local intensity histograms and built upon(More)
Abstract. To achieve sparse parametrizations that allows intuitive analysis, we aim to represent deformation with a basis containing interpretable elements, and we wish to use elements that have the description capacity to represent the deformation compactly. To accomplish this, we introduce in this paper higher-order momentum distributions in the LDDMM(More)
Mutual Information (MI) and normalized mutual information (NMI) are popular choices as similarity measure for multimodal image registration. Presently, one of two approaches is often used for estimating these measures: The Parzen Window (PW) and the Generalized Partial Volume (GPV). Their theoretical relation has so far been unexplored. We present the(More)
Statistical region-based segmentation methods such as the Active Appearance Model (AAM) are used for establishing dense correspondences in images based on learning the variation in shape and pixel intensities in a training set. For low resolution 2D images correspondences can be recovered reliably in real-time. However, as resolution increases this becomes(More)
Precise and robust whole brain, ventricle, and hippocampal atrophy measurements are important as they serve as biomarkers for Alzheimer’s disease. They are used as secondary outcomes in drug trials, and they correlate with the cognitive scores. When two successive scans are non-linearly aligned by registration, the volume change in a region of interest(More)
Many hearing aid users experience physical discomfort when wearing their device. The main contributor to this problem is believed to be deformation of the ear and ear canal caused by movement of the mandible. Physical discomfort results from added pressure on soft tissue areas in the ear. Identifying features that can predict potential deformation is(More)