Kalle Åström
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View article: Longitudinal outcome prediction of prostate cancer patients on active surveillance using multiple instance learning
Longitudinal outcome prediction of prostate cancer patients on active surveillance using multiple instance learning Open
We show that avoiding Gleason grades is beneficial for longitudinal outcome prediction of prostate cancer. Our results suggest that benign prostate tissue contains prognostic information. However, before our models could be used clinically…
View article: Reference proteins to improve Core 1 and Core 2 Alzheimer’s disease CSF and plasma biomarkers
Reference proteins to improve Core 1 and Core 2 Alzheimer’s disease CSF and plasma biomarkers Open
Concentration-based fluid biomarkers represent an informative and cost-effective way to detect and monitor Alzheimer’s disease (AD) pathology. However, non-AD-related inter-individual variation in biofluids can also affect biomarker concen…
View article: Sparse Multiview Open-Vocabulary 3D Detection
Sparse Multiview Open-Vocabulary 3D Detection Open
The ability to interpret and comprehend a 3D scene is essential for many vision and robotics systems. In numerous applications, this involves 3D object detection, i.e.~identifying the location and dimensions of objects belonging to a speci…
View article: Converting T1-weighted MRI from 3T to 7T quality using deep learning
Converting T1-weighted MRI from 3T to 7T quality using deep learning Open
Ultra-high resolution 7 tesla (7T) magnetic resonance imaging (MRI) provides detailed anatomical views, offering better signal-to-noise ratio, resolution and tissue contrast than 3T MRI, though at the cost of accessibility. We present an a…
View article: Machine learning prediction of tau‐PET in Alzheimer's disease using plasma, MRI, and clinical data
Machine learning prediction of tau‐PET in Alzheimer's disease using plasma, MRI, and clinical data Open
INTRODUCTION Tau positron emission tomography (PET) is a reliable neuroimaging technique for assessing regional load of tau pathology in the brain, but its routine clinical use is limited by cost and accessibility barriers. METHODS We thor…
View article: Breast cancer classification in point-of-care ultrasound imaging—the impact of training data
Breast cancer classification in point-of-care ultrasound imaging—the impact of training data Open
Applying augmentation during training showed to be important and increased the performance of the classification network. Adding more data also increased the performance, but using standard US images or CycleGAN-generated POCUS images gave…
View article: Single-Source Localization as an Eigenvalue Problem
Single-Source Localization as an Eigenvalue Problem Open
This paper introduces a novel method for solving the single-source localization problem, specifically addressing the case of trilateration. We formulate the problem as a weighted least-squares problem in the squared distances and demonstra…
View article: Improved precision of Alzheimer’s disease fluid biomarkers when using Amyloid‐β<sub>40</sub> or non‐phosphorylated tau as a reference
Improved precision of Alzheimer’s disease fluid biomarkers when using Amyloid‐β<sub>40</sub> or non‐phosphorylated tau as a reference Open
Background Fluid biomarkers represent an informative and cost‐effective way to detect and monitor Alzheimer’s disease (AD). However, as we recently showed, the overall proteome average in CSF exhibits a non‐disease related average signal (…
View article: Unlocking Tau PET Accessibility: a Machine Learning‐Based Prediction of Tau Pathology from Plasma, MRI and Clinical Variables
Unlocking Tau PET Accessibility: a Machine Learning‐Based Prediction of Tau Pathology from Plasma, MRI and Clinical Variables Open
Background A key characteristic of Alzheimer’s disease (AD) is cerebral aggregation of tau. These aggregates can be quantified and localized with positron emission tomography (PET), which improves the diagnostic and prognostic work‐up of A…
View article: SONNET: Enhancing Time Delay Estimation by Leveraging Simulated Audio
SONNET: Enhancing Time Delay Estimation by Leveraging Simulated Audio Open
Time delay estimation or Time-Difference-Of-Arrival estimates is a critical component for multiple localization applications such as multilateration, direction of arrival, and self-calibration. The task is to estimate the time difference b…
View article: The Impact of Semi-Supervised Learning on Line Segment Detection
The Impact of Semi-Supervised Learning on Line Segment Detection Open
In this paper we present a method for line segment detection in images, based on a semi-supervised framework. Leveraging the use of a consistency loss based on differently augmented and perturbed unlabeled images with a small amount of lab…
View article: Learning Multi-Target TDOA Features for Sound Event Localization and Detection
Learning Multi-Target TDOA Features for Sound Event Localization and Detection Open
Sound event localization and detection (SELD) systems using audio recordings from a microphone array rely on spatial cues for determining the location of sound events. As a consequence, the localization performance of such systems is to a …
View article: wav2pos: Sound Source Localization using Masked Autoencoders
wav2pos: Sound Source Localization using Masked Autoencoders Open
We present a novel approach to the 3D sound source localization task for distributed ad-hoc microphone arrays by formulating it as a set-to-set regression problem. By training a multi-modal masked autoencoder model that operates on audio r…
View article: Artificial intelligence for detection of prostate cancer in biopsies during active surveillance
Artificial intelligence for detection of prostate cancer in biopsies during active surveillance Open
Objectives To evaluate a cancer detecting artificial intelligence (AI) algorithm on serial biopsies in patients with prostate cancer on active surveillance (AS). Patients and methods A total of 180 patients in the Prostate Cancer Research …
View article: A machine learning-based prediction of tau load and distribution in Alzheimer’s disease using plasma, MRI and clinical variables
A machine learning-based prediction of tau load and distribution in Alzheimer’s disease using plasma, MRI and clinical variables Open
Tau positron emission tomography (PET) is a reliable neuroimaging technique for assessing regional load of tau pathology in the brain, commonly used in Alzheimer’s disease (AD) research and clinical trials. However, its routine clinical us…
View article: Cerebrospinal fluid reference proteins increase accuracy and interpretability of biomarkers for brain diseases
Cerebrospinal fluid reference proteins increase accuracy and interpretability of biomarkers for brain diseases Open
Cerebrospinal fluid (CSF) biomarkers reflect brain pathophysiology and are used extensively in translational research as well as in clinical practice for diagnosis of neurological diseases, e.g., Alzheimer’s disease (AD). However, CSF biom…
View article: NeuroNCAP: Photorealistic Closed-loop Safety Testing for Autonomous Driving
NeuroNCAP: Photorealistic Closed-loop Safety Testing for Autonomous Driving Open
We present a versatile NeRF-based simulator for testing autonomous driving (AD) software systems, designed with a focus on sensor-realistic closed-loop evaluation and the creation of safety-critical scenarios. The simulator learns from seq…
View article: GCC-PHAT Re-Imagined - A U-Net Filter for Audio TDOA Peak-Selection
GCC-PHAT Re-Imagined - A U-Net Filter for Audio TDOA Peak-Selection Open
Time-difference-of-arrival (TDOA) estimation from GCC-PHAT is not always as straight forward as finding the maximum peak. This work views the GCC output as an image, with time on the vertical axis and TDOA horizontally, to explore if image…
View article: LuViRA Dataset Validation and Discussion: Comparing Vision, Radio, and Audio Sensors for Indoor Localization
LuViRA Dataset Validation and Discussion: Comparing Vision, Radio, and Audio Sensors for Indoor Localization Open
We present a unique comparative analysis, and evaluation of vision, radio, and audio based localization algorithms. We create the first baseline for the aforementioned sensors using the recently published Lund University Vision, Radio, and…
View article: Estimates of Temporal Edge Detection Filters in Human Vision
Estimates of Temporal Edge Detection Filters in Human Vision Open
Edge detection is an important process in human visual processing. However, as far as we know, few attempts have been made to map the temporal edge detection filters in human vision. To that end, we devised a user study and collected data …
View article: Geometry-Biased Transformer for Robust Multi-View 3D Human Pose Reconstruction
Geometry-Biased Transformer for Robust Multi-View 3D Human Pose Reconstruction Open
We address the challenges in estimating 3D human poses from multiple views under occlusion and with limited overlapping views. We approach multi-view, single-person 3D human pose reconstruction as a regression problem and propose a novel e…
View article: Comparing a pre-defined versus deep learning approach for extracting brain atrophy patterns to predict cognitive decline due to Alzheimer’s disease in patients with mild cognitive symptoms
Comparing a pre-defined versus deep learning approach for extracting brain atrophy patterns to predict cognitive decline due to Alzheimer’s disease in patients with mild cognitive symptoms Open
Background : Predicting future Alzheimer’s disease (AD)-related cognitive decline among individuals with subjective cognitive decline (SCD) or mild cognitive impairment (MCI) is an important task for healthcare. Structural brain imaging as…
View article: LuViRA Dataset Validation and Discussion: Comparing Vision, Radio, and Audio Sensors for Indoor Localization
LuViRA Dataset Validation and Discussion: Comparing Vision, Radio, and Audio Sensors for Indoor Localization Open
We present a unique comparative analysis, and evaluation of vision, radio, and audio based localization algorithms. We create the first baseline for the aforementioned sensors using the recently published Lund University Vision, Radio, and…