Deep learning‐based whole‐brain B1+‐mapping at 7T

F Krueger, CS Aigner, M Lutz… - Magnetic …, 2024 - Wiley Online Library
Purpose This study investigates the feasibility of using complex‐valued neural networks
(NNs) to estimate quantitative transmit magnetic RF field (B1+) maps from multi‐slice …

Investigation of alternative RF power limit control methods for 0.5 T, 1.5 T, and 3T parallel transmission cardiac imaging: A simulation study

J Petzold, S Schmitter, B Silemek… - Magnetic …, 2024 - Wiley Online Library
Purpose To investigate safety and performance aspects of parallel‐transmit (pTx) RF control‐
modes for a body coil at B 0≤ 3 TB _0 ≤ 3 T. Methods Electromagnetic simulations of 11 …

A 3D surface coil with deep learning‐based noise reduction for parotid gland imaging at 7T

S Gokyar, C Zhao, S Gunamony, L Tang, J West… - …, 2024 - Wiley Online Library
Abstract Background Background: Parotid gland neoplasms occur near the facial nerve.
Hence, it is crucial to determine whether the malignant neoplasms involve the facial nerve …

Deep Dive into MRI: Exploring Deep Learning Applications in 0.55 T and 7T MRI

AC Alves, A Ferreira, B Puladi, J Egger… - arXiv preprint arXiv …, 2024 - arxiv.org
The development of magnetic resonance imaging (MRI) for medical imaging has provided a
leap forward in diagnosis, providing a safe, non-invasive alternative to techniques involving …

Knee Model Construction Using Deep Neural Networks with Boundary Information for Local SAR Estimation

L Xiao, H Ren, H Zhou, C Xing - Applied Magnetic Resonance, 2024 - Springer
The local specific absorption rate (SAR) is a key safety indicator in high-field MRI.
Constructing a specific model for each patient is important for accurate estimation of local …

[PDF][PDF] On radio-frequency implant safety in parallel transmission MRI

J Petzold - 2024 - opendata.uni-halle.de
The rising count of patients bearing an active implantable medical device (AIMD) are often
hindered from having magnetic resonance (MR) exams because MR-unsafe implants can …

[PDF][PDF] Feasibility of predicting MRI tissue heating (MRSaiFE) using experimental training data

M Zhang, N Panjwani, E Motovilova, J Dyke, F Robb… - winklerlab.weill.cornell.edu
Feasibility of predicting MRI tissue heating (MRSaiFE) using experimental training data Page 1
11/8/23, 2:34 PM submissions.mirasmart.com/ISMRM2024/ViewSubmission.aspx?sbmID=8102 …

[PDF][PDF] Tailored dielectric shimming in MRI using machine learning-a feasibility study

M Zhang, N Panjwani, E Motovilova, J Dyke, F Robb… - winklerlab.weill.cornell.edu
Motivation: Inhomogeneities of the MRI transmit íeld cause image shading and hinder
diagnosis. In dielectric shimming, pads of high permittivity are used to recover signal in low …