Publication

A step forward to improve large numerical phantoms at the microstructure level using CACTUS

Jean-Philippe Thiran
2023

Abstract

Inferring microscopic tissue properties from the measured signal is one of the main objectives of diffusion-weighted magnetic resonance imaging. The use of Monte-Carlo Simulations for DW-MRI on realistic substrates will help the study of DWI-MRI signals in controlled environments and investigate, extract, and validate approaches for the understanding of white matter features. This work provides a unique framework for building complex white matter phantoms with novel properties, such as 1) substrates with a high packing density of 95% intra-axonal volume percentage and substrate sizes of (500 um)3, 2) Create, generalise, extend, and preexisting phantom configurations used by other studies.

Official source

https://infoscience.epfl.ch/entities/publication/994dc62d-0fea-445d-ac4b-22bcdbb106a8

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Jean-Philippe Thiran
2023

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/994dc62d-0fea-445d-ac4b-22bcdbb106a8

About this result

Related concepts (30)

Diffusion MRI

Diffusion-weighted magnetic resonance imaging (DWI or DW-MRI) is the use of specific MRI sequences as well as software that generates images from the resulting data that uses the diffusion of water molecules to generate contrast in MR images. It allows the mapping of the diffusion process of molecules, mainly water, in biological tissues, in vivo and non-invasively. Molecular diffusion in tissues is not random, but reflects interactions with many obstacles, such as macromolecules, fibers, and membranes.

Connectome

A connectome (kəˈnɛktoʊm) is a comprehensive map of neural connections in the brain, and may be thought of as its "wiring diagram". An organism's nervous system is made up of neurons which communicate through synapses. A connectome is constructed by tracing the neuron in a nervous system and mapping where neurons are connected through synapses. The significance of the connectome stems from the realization that the structure and function of the human brain are intricately linked, through multiple levels and modes of brain connectivity.

Signal

In signal processing, a signal is a function that conveys information about a phenomenon. Any quantity that can vary over space or time can be used as a signal to share messages between observers. The IEEE Transactions on Signal Processing includes audio, video, speech, , sonar, and radar as examples of signals. A signal may also be defined as observable change in a quantity over space or time (a time series), even if it does not carry information.

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A step forward to improve large numerical phantoms at the microstructure level using CACTUS

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