Advances in multimodal data fusion in neuroimaging: overview, challenges, and novel orientation

YD Zhang, Z Dong, SH Wang, X Yu, X Yao, Q Zhou… - Information …, 2020 - Elsevier
Multimodal fusion in neuroimaging combines data from multiple imaging modalities to
overcome the fundamental limitations of individual modalities. Neuroimaging fusion can …

A review of deep-learning-based approaches for attenuation correction in positron emission tomography

JS Lee - IEEE Transactions on Radiation and Plasma Medical …, 2020 - ieeexplore.ieee.org
Attenuation correction (AC) is essential for the generation of artifact-free and quantitatively
accurate positron emission tomography (PET) images. PET AC based on computed …

EANM procedure guidelines for brain PET imaging using [18F]FDG, version 3

E Guedj, A Varrone, R Boellaard, NL Albert… - European journal of …, 2022 - Springer
The present procedural guidelines summarize the current views of the EANM Neuro-
Imaging Committee (NIC). The purpose of these guidelines is to assist nuclear medicine …

Joint EANM/EANO/RANO practice guidelines/SNMMI procedure standards for imaging of gliomas using PET with radiolabelled amino acids and [18F]FDG: version …

I Law, NL Albert, J Arbizu, R Boellaard… - European journal of …, 2019 - Springer
These joint practice guidelines, or procedure standards, were developed collaboratively by
the European Association of Nuclear Medicine (EANM), the Society of Nuclear Medicine and …

Deep learning MR imaging–based attenuation correction for PET/MR imaging

F Liu, H Jang, R Kijowski, T Bradshaw, AB McMillan - Radiology, 2018 - pubs.rsna.org
Purpose To develop and evaluate the feasibility of deep learning approaches for magnetic
resonance (MR) imaging–based attenuation correction (AC)(termed deep MRAC) in brain …

Tau deposition patterns are associated with functional connectivity in primary tauopathies

N Franzmeier, M Brendel, L Beyer, L Slemann… - Nature …, 2022 - nature.com
Tau pathology is the main driver of neuronal dysfunction in 4-repeat tauopathies, including
cortico-basal degeneration and progressive supranuclear palsy. Tau is assumed to spread …

Using domain knowledge for robust and generalizable deep learning-based CT-free PET attenuation and scatter correction

R Guo, S Xue, J Hu, H Sari, C Mingels… - Nature …, 2022 - nature.com
Despite the potential of deep learning (DL)-based methods in substituting CT-based PET
attenuation and scatter correction for CT-free PET imaging, a critical bottleneck is their …

Dixon-VIBE deep learning (DIVIDE) pseudo-CT synthesis for pelvis PET/MR attenuation correction

A Torrado-Carvajal, J Vera-Olmos… - Journal of nuclear …, 2019 - Soc Nuclear Med
Whole-body attenuation correction (AC) is still challenging in combined PET/MR scanners.
We describe Dixon-VIBE Deep Learning (DIVIDE), a deep-learning network that allows …

[HTML][HTML] Multimodal comparisons of QSM and PET in neurodegeneration and aging

PM Cogswell, AP Fan - NeuroImage, 2023 - Elsevier
Quantitative susceptibility map** (QSM) has been used to study susceptibility changes
that may occur based on tissue composition and mineral deposition. Iron is a primary …

A deep learning approach for 18F-FDG PET attenuation correction

F Liu, H Jang, R Kijowski, G Zhao, T Bradshaw… - EJNMMI physics, 2018 - Springer
Background To develop and evaluate the feasibility of a data-driven deep learning approach
(deepAC) for positron-emission tomography (PET) image attenuation correction without …