Related papers: Simulation and Harmonic Analysis of k-Space Readou…
We propose a new, modular, open-source, Python-based 3D+time fMRI data simulation software, \emph{SNAKE-fMRI}, which stands for \emph{S}imulator from \emph{N}eurovascular coupling to \emph{A}cquisition of \emph{K}-space data for…
Designing a robotic system that functions effectively within the specific environment of a Magnetic Resonance Imaging (MRI) scanner requires solving numerous technical issues, such as maintaining the robot's precision and stability under…
MATI (Microstructural Analysis Toolbox for Imaging) is a versatile MATLAB-based toolbox that combines both simulation and data fitting capabilities for microstructural dMRI research. It provides a user-friendly, GUI-driven interface that…
Accurate MR signal simulation, including microvascular structures and water diffusion, is crucial for MRI techniques like fMRI BOLD modeling and MR vascular Fingerprinting (MRF), which use susceptibility effects on MR signals for tissue…
In this paper, we present a machine learning-based data generator framework tailored to aid researchers who utilize simulations to examine various physical systems or processes. High computational costs and the resulting limited data often…
Purpose: Conventional MRI is relying on the assumption of the magnetic field being homogeneous in direction and amplitude. However, with the growing interest in portable, affordable point-of-care MRI systems, these assumptions do not…
We present M-SPARC: MATLAB-Simulation Package for Ab-initio Real-space Calculations. It can perform pseudopotential spin-polarized and unpolarized Kohn-Sham Density Functional Theory (DFT) simulations for isolated systems such as molecules…
Background: Magnetic Resonance Imaging (MRI) is a medical imaging technique that combines principles of physics, math, and engineering to look inside humans and animals, hence delivering a lifesaving technology. However, resource-poor…
In this paper, we present MASTISK (MAchine-learning and Synaptic-plasticity Technology Integrated Simulation frameworK). MASTISK is an open-source versatile and flexible tool developed in MATLAB for design exploration of dedicated…
We present a data simulation package designed to create a series of simulated data samples for a detector with non-destructive sampling capability. The original intent of this software was to provide a method for generating simulated images…
Modelling complex real-world situations such as infectious diseases, geological phenomena, and biological processes can present a dilemma: the computer model (referred to as a simulator) needs to be complex enough to capture the dynamics of…
State Space Models (SSM) is a MATLAB 7.0 software toolbox for doing time series analysis by state space methods. The software features fully interactive construction and combination of models, with support for univariate and multivariate…
In research activities regarding Magnetic Resonance Imaging in medicine, simulation tools with a universal approach are rare. Usually, simulators are developed and used which tend to be restricted to a particular, small range of…
As deep neural networks require tremendous amount of computation and memory, analog computing with emerging memory devices is a promising alternative to digital computing for edge devices. However, because of the increasing simulation time…
Line laser scanners are a sub-type of structured light 3D scanners that are relatively common devices to find within the industrial setting, typically in the context of assembly, process control, and welding. Despite its extensive use,…
MR Fingerprinting is a novel quantitative MR technique that could simultaneously provide multiple tissue property maps. When optimizing MRF scans, modeling undersampling errors and field imperfections in cost functions will make the…
Supervised deep learning methods typically rely on large datasets for training. Ethical and practical considerations usually make it difficult to access large amounts of healthcare data, such as medical images, with known task-specific…
Background and Objective: Computational ultrasound imaging has become a well-established methodology in the ultrasound community. Simulations of ultrasound sequences and images allow the study of innovative techniques in terms of emission…
First-time patients undergoing diagnostic computed tomography (CT) scans often experience significant anxiety and uncertainty, which can negatively impact scan results and patient well-being. We present an immersive mixed reality (MR)…
Developing dedicated mixed-signal neuromorphic computing systems optimized for real-time sensory-processing in extreme edge-computing applications requires time-consuming design, fabrication, and deployment of full-custom neuromorphic…