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Objectives: To evaluate the feasibility of AI-assisted reading of prostate magnetic resonance imaging (MRI) in Organized Prostate cancer Testing (OPT). Methods: Retrospective cohort study including 57 men with elevated prostate-specific antigen (PSA) levels ≥3 µg/L that performed bi-parametric MRI in OPT. The results of a CE-marked deep learning (DL) algorithm for prostate MRI lesion detection wer
Semi-arid ecosystems, common across the Australian continent, strongly influence the inter-annual variability and trend in the global terrestrial net carbon sink. Here we explore the future Australian terrestrial carbon cycle using the CMIP6 ensemble, and the dynamic global vegetation model LPJ-GUESS. Uncertainty in Australia's carbon storage in vegetation ranged between 6 and 49 PgC at the end of
The separation of multiple transmit waveforms with time and frequency synchronization constitutes a considerable challenge for multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) systems. It is well-known that aliased signal returns may be separable by digital beamforming (DBF) on receive in elevation. However, the current orthogonal-waveform beamforming schemes significantly incr
Background: Chronic obstructive pulmonary disease (COPD) is a severe condition affecting millions worldwide, leading to numerous annual deaths. The absence of significant symptoms in its early stages promotes high underdiagnosis rates for the affected people. Besides pulmonary function failure, another harmful problem of COPD is the systemic effects, e.g., heart failure or voice distortion. Howeve
This work investigates the design of beampatterns for frequency diverse arrays-multiple-input multiple-output (FDA-MIMO) in the range-angle plane, in order to improve the approximation of a desired beampattern. Recognizing that the energy radiated by the array cannot be locked at a fixed range and angle, the beampattern is designed for the equivalent beampattern at the receiving end, differing fro
This thesis investigates the role of advanced atmospheric inversion techniques and ∆¹⁴CO₂ observations in improving the accuracy of regional CO₂ flux estimates across Europe. Accurate quantification of fossil fuel emissions and biospheric fluxes is essential for understanding regional carbon budgets and supporting climate policy. However, significant uncertainties persist due to limited observatio
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 between a signal arriving at two different sensors. For the audio sensor modality, most current systems are based on classical methods such as the Generalized Cro
This paper suggests an approach to solving the time-of-arrival self-calibration problem for imbalanced problems, where there is a low number of receivers but many senders. The idea is to solve several subproblems created by only using data relating to four receivers. The solutions are then clustered according to a proposed metric in order to remove failed reconstructions. They are then combined in
Non-invasive evaluation of glymphatic function has emerged as a crucial goal in neuroimaging, and diffusion tensor imaging along the perivascular space (DTI-ALPS) has emerged as a candidate method for this purpose. Reduced ALPS index has been suggested to indicate impaired glymphatic function. However, the potential impact of crossing fibres on the ALPS index has not been assessed, which was the a
Background/objectives: Mycosis fungoides (MF) is a rare malignancy, with an indolent course in the early stages of the disease. However, due to major molecular and clinical heterogeneity, patients at an advanced stage of the disease have variable responses to treatment and considerably reduced life expectancy. Today, there is a lack of specific markers for the progression from early to advanced st
When processing radar signals, the target steering vector is generally only partially known, being subject to various forms of errors and mismatches. In this article, we investigate the design of an unimodular transmit sequence that is robust against steering vector mismatches, with the aim of enhancing the performance of a frequency diverse array multiple-input-multiple-output (FDA-MIMO) radar sy
Climate-vegetation feedbacks (CVFs) can amplify or mitigate climate variations. These feedbacks operate at multiple timescales. Fast processes such as leaf-scale carbon fluxes operate at sub-annual timescales, while slow processes, driven by changes in forest composition and structure, occur over decadal and longer timescales. Slow processes are rarely directly observed from instrumental data; yet
Land cover governs biogeophysical and biogeochemical feedbacks between the land surface and atmosphere. Holocene vegetation-atmosphere interactions are of particular interest, both to understand the climate effects of intensifying human land use and as a possible explanation for the Holocene Conundrum, a widely studied mismatch between simulated and reconstructed temperatures. Progress addressing
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 demonstrate how suitable weights are chosen to accommodate different noise distributions. By transforming this formulation into an eigenvalue problem, we leverage existin
Motivation: Pollinators play a crucial role in maintaining Earth's terrestrial biodiversity. However, rapid human-induced environmental changes are compromising the long-term persistence of plant-pollinator interactions. Unfortunately, we lack robust, generalisable data capturing how plant-pollinator communities are structured across space and time. Here, we present the EuPPollNet (European Plant-
The distinguishing feature of frequency diverse array (FDA) systems as compared to conventional phased-array and multiple-input multiple-output (MIMO) radar systems is the use of a small frequency offset (FO) across the array elements. Much of the development to date has focused on the FDA-MIMO structure, using an FO that is larger than the bandwidth of the baseband signal, thereby reducing the re
Research connecting text and images has recently seen several breakthroughs, with models like CLIP, DALL•E 2, and Stable Diffusion. However, the connection between text and other visual modalities, such as lidar data, has received less attention, prohibited by the lack of text-lidar datasets. In this work, we propose LidarCLIP, a mapping from automotive point clouds to a pre-existing CLIP embeddin
