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Functional magnetic resonance imaging (fMRI) is a non-invasive and in-vivo imaging technique essential for measuring brain activity. Functional connectivity is used to study associations between brain regions, either while study subjects…
Feature pyramid network (FPN) is a critical component in modern object detection frameworks. The performance gain in most of the existing FPN variants is mainly attributed to the increase of computational burden. An attempt to enhance the…
This paper describes the mapmaking procedure applied to Planck LFI (Low Frequency Instrument) data. The mapmaking step takes as input the calibrated timelines and pointing information. The main products are sky maps of $I,Q$, and $U$ Stokes…
The use of engineered nanoscale magnetic materials in healthcare and biomedical technologies is rapidly growing. Two examples which have recently attracted significant attention are magnetic particle imaging (MPI) for biological monitoring,…
In this paper, we provide expressions for the detected optical irradiance for magneto-optic characterization of superparamagnetic nanoparticles (SPNs) in solution imparting Faraday rotation (FR) to an optical beam passing through the sample…
Since the initial patent in 2001, the Magnetic Particle Imaging (MPI) community has been striving to develop an MPI scanner suitable for human applications. Numerous contributions from different research fields, regarding tracer…
To date, several methods have been developed to explain deep learning algorithms for classification tasks. Recently, an adaptation of two of such methods has been proposed to generate instance-level explainable maps in a semantic…
We have developed the experimental approach to characterize spatial distribution of the magnetic field produced by cantilever tips used in magnetic resonance force microscopy (MRFM). We performed MRFM measurements on a well characterized…
We propose a method for estimating more reproducible functional networks that are more strongly associated with dynamic task activity by using recurrent neural networks with long short term memory (LSTMs). The LSTM model is trained in an…
Magnetic Particle Imaging (MPI) is a preclinical imaging technique capable of visualizing the spatio-temporal distribution of magnetic nanoparticles. The image reconstruction of this fast and dynamic process relies on efficiently solving an…
Proton imaging is a powerful tool for probing electromagnetic fields in a plasma, providing a path-integrated map of the field topology. However, in cases where the field structure is highly inhomogeneous, inferring spatial properties of…
Radio maps are essential for enhancing wireless communications and localization. However, existing methods for constructing radio maps typically require costly calibration processes to collect location-labeled channel state information…
We present an automatized approach towards maximally localized Wannier functions (MLWFs) applicable to both occupied and unoccupied states. We overcome limitations of the standard optimized projection function (OPF) method and its…
The development of ferromagnet/heavy metal thin-film structures, such as CoFeB/Mo, with spin-orbit interaction requires advanced methods for their production and study. Polarized neutron reflectometry (PNR) provides unique insights into the…
We report the local measurements of the magnetic penetration depth $\lambda$ in a superconducting Nb film using magnetic force microscopy (MFM). We developed a method for quantitative extraction of the penetration depth from…
Model-driven analysis of biophysical phenomena is gaining increased attention and utility for medical imaging applications. In magnetic resonance imaging (MRI), the availability of well-established models for describing the relations…
This paper introduces a novel framework for image quality transfer based on conditional flow matching (CFM). Unlike conventional generative models that rely on iterative sampling or adversarial objectives, CFM learns a continuous flow…
Traditional molecule generation methods often rely on sequence- or graph-based representations, which can limit their expressive power or require complex permutation-equivariant architectures. This paper introduces a novel paradigm for…
Reconstructing magnetization in nanoscale magnetic thin films is essential for developing next-generation memory, sensors, and various spintronic technologies. However, this remains challenging due to the ill-posed nature of the stray field…
The modulation transfer function (MTF) represents the frequency domain response of imaging modalities. Here, we report a method for estimating the MTF from sample images. Test images were generated from a number of images, including those…