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We developed an automatic algorithm with the purpose to assist pathologists to report Gleason score on malignant prostatic adenocarcinoma specimen. In order to detect and classify the cancerous tissue, a deep convolutional neural network that had been pre-trained on a large set of photographic images was used. A specific aim was to support intuitive interaction with the result, to let pathologist
Indoor positioning for smart phone users has received a lot of attention in recent years. While many solutions have been developed, most rely on extra sensors, a need for predeployment of infrastructure or collecting ground truth data to train on. In this paper we see what can be done using only existing WiFi-infrastructure and Received Signal Strength from these, not using any extra sensors or ca
A well-planned waiting area is crucial for automatic milking systems. In an enclosed waiting area, cows of different rank compete for entering the milking station and they are exposed for a variety of social interactions. Such interactions could increase standing time and delay milking, which may result in stress, lameness, impaired welfare and reduced performance. The aim was to monitor the waiti
The field of high dynamic range imaging addresses the problem of capturing and displaying the large range of luminance levels found in the world, using devices with limited dynamic range. In this paper we present a novel tone mapping algorithm that is based on K-means clustering. Using dynamic programming we are able to not only solve the clustering problem efficiently, but also find the global op
In this paper we present a system for performing low rank matrix factorization. Low-rank matrix factorization is an essential problem in many areas including computer vision, with applications in e.g. affine structure-from-motion, photometric stereo, and non-rigid structure from motion. We specifically target structured data patterns, with outliers and large amounts of missing data. Using recently
The central problem of this thesis is locating several sources and simultaneously locating the positions of the sensors. The measurements captured by the sensors are time of arrival (TOA), time difference of arrival (TDOA), unsynchronized TDOA, or received signal strength indication (RSSI), all a variation of distance measurement between sensors and sources. Signals can be either sound or radio fo
A large number of medical examinations involve images in some way. Images can be used for diagnostics, follow-up studies and treatment planning. In this thesis mathematical methods have been developed and adapted in order to analyze medical images. Several applications for different imaging modalities have been studied and the usefulness of such methods is demonstrated.A complete system for detect
In this paper we study symmetries in polynomial equation systems and how they can be integrated into the action matrix method. The main contribution is a generalization of the partial p-fold symmetry and we provide new theoretical insights as to why these methods work. We show several examples of how to use this symmetry to construct more compact polynomial solvers. As a second contribution we pre
In this paper, we focus on solving the time delay as a separateproblem to the reconstruction of the microphone and sound locations.The time delay estimation appears as one of the main steps in sensorcalibration problem, once the time delays are known or estimated, wecan solve the time-difference-of-arrival problems by converting them totime-of-arrival problems. In this paper we make use of an alte
In this paper we present a novel, fast and accurate system for detecting the presence of cars in parking lots. The system is based on fast integral channel features and machine learning. The methods are well suited for running embedded on low performance platforms. The methods are tested on a database of nearly 700,000 images of parking spaces, where 48.5% are occupied and the rest are free. The e
The problem of estimating receiver-sender node positionsfrom measured receiver-sender distances is a key issue indifferent applications such as microphone array calibration, radioantenna array calibration, mapping and positioning using ultrawidebandand mapping and positioning using round-trip-timemeasurements between mobile phones and Wi-Fi-units. Thanks torecent research in this area we have an i
Indoor positioning for smartphone usershas received a lot of attention in recent years. Whilemany solutions have been developed, most rely on aneed for pre-deployment of infrastructure or collectingground truth data to train on. In this paper we see whatcan be done using existing WiFi-infrastructure andReceived Signal Strength from these to smartphones,not using any calibration of the signal envir
We present a minimal solver for a special kind of homography arising in applications with planar camera motion (e.g. mobile robotics applications). Since the camera motion we consider only has five degrees of freedom, an explicit parametrisation allows us to reduce the required number of point correspondences to 2.5. Using fewer point correspondences is beneficial when used together with RANSAC, b
Due to advances in technology the amount of images from portable cameras has increased tremendously in recent years. Nowadays, most new mobile phones and cars have multiple cameras. Drones and other robots are often equipped with cameras as well. To be able to capture an image is not the same as to understand the content of it. Computer vision deals with the task of giving machines the ability to
BACKGROUND: Parkinson's disease has been reported in a small number of patients with chromosome 22q11.2 deletion syndrome. In this study, we screened a series of large, independent Parkinson's disease case-control studies for deletions at 22q11.2.METHODS: We used data on deletions spanning the 22q11.2 locus from four independent case-control Parkinson's disease studies (UK Wellcome Trust Case Cont
OBJECTIVE: Huntington disease (HD) is a fatal autosomal dominant, neurodegenerative condition characterized by progressively worsening motor and nonmotor problems including cognitive and neuropsychiatric disturbances, along with sleep abnormalities and weight loss. However, it is not known whether sleep disturbances and metabolic abnormalities underlying the weight loss are present at a premanifes
Genetic variation is associated with differences in the function of the brain as well as its susceptibility to disease. The common H1 haplotypic variant of the microtubule-associated protein tau gene (MAPT) has been related to an increased risk for Parkinson's disease (PD). Furthermore, among PD patients, H1 homozygotes have an accelerated progression to dementia. We investigated the neurocognitiv
Understanding the trade-off between energy expenditure of carrying large fuel loads and the risk of fuel depletion is imperative to understand the evolution of flight strategies during long-distance animal migration. Global flyways regularly involve sea crossings that may impose flight prolongations on migrating land-birds and thereby reduce their energy reserves and survival prospects. We studied
IMPORTANCE AND AIMS: Diabetic microvascular complications significantly impact morbidity and mortality. This review focuses on machine learning/artificial intelligence (ML/AI) in predicting diabetic retinopathy (DR), diabetic kidney disease (DKD), and diabetic neuropathy (DN).METHODS: A comprehensive PubMed search from 1990 to 2023 identified studies on ML/AI models for diabetic microvascular comp
Brain cell structure and function reflect neurodevelopment, plasticity, and aging; and changes can help flag pathological processes such as neurodegeneration and neuroinflammation. Accurate and quantitative methods to noninvasively disentangle cellular structural features are needed and are a substantial focus of brain research. Diffusion-weighted MRS (dMRS) gives access to diffusion properties of
