Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.0
3.8
Journals
Bioengineering
Special Issues
Advances in Brain Magnetic Resonance Imaging
share announcement

Advances in Brain Magnetic Resonance Imaging

A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biosignal Processing".

Deadline for manuscript submissions: closed (15 November 2024) | Viewed by 2403

Special Issue Editors

Dr. Hongjiang Wei

E-Mail Website
Guest Editor
School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
Interests: MRI; medical image analysis
Dr. Yang Gao

E-Mail Website
Guest Editor
Computer Science Department, Central South University, Changsha, China
Interests: brain MRI; machine learning

Special Issue Information

Dear Colleagues,

We are pleased to invite you to contribute to a Special Issue focused on the cutting-edge advancements in Brain MRI, encompassing innovative imaging methods, state-of-the-art MRI reconstruction techniques, and sophisticated MRI data analysis approaches.

Magnetic Resonance Imaging (MRI) has played a pivotal role in revolutionizing our understanding of the brain's structure and function. In recent years, significant strides have been made in this field, offering exciting opportunities for bioengineers and researchers to delve into the complexities of brain imaging. This Special Issue aims to provide a platform for sharing groundbreaking discoveries related to Brain MRI. We welcome submissions on a wide range of topics, including but not limited to:

  • Novel Brain MRI Acquisition Techniques;
  • Advanced MRI Reconstruction Algorithms;
  • Quantitative Susceptibility Mapping (QSM) and Phase Imaging;
  • Functional MRI (fMRI) and Connectivity Analysis;
  • Machine learning and deep learning Applications in MRI Analysis;
  • Neuroimaging Biomarkers for Disease Diagnosis and Progression;
  • Multimodal Imaging Integration and Fusion;
  • Clinical Applications of Brain MRI.

We encourage submissions that showcase interdisciplinary collaborations. We look forward to receiving your manuscripts and sharing your groundbreaking work with our readers.

Dr. Hongjiang Wei
Dr. Yang Gao
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Bioengineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

14 pages, 3952 KiB  
Article
Multivariate Analyses with Two-Step Dimension Reduction for an Association Study Between 11C-Pittsburgh Compound B and Magnetic Resonance Imaging in Alzheimer’s Disease
by Atsushi Kawaguchi and Fumio Yamashita
Bioengineering 2025, 12(1), 48; https://doi.org/10.3390/bioengineering12010048 - 9 Jan 2025
Viewed by 700
Abstract
The neuropathological diagnosis of Alzheimer’s disease (AD) relies on amyloid beta (Aβ) deposition in brain tissues. To study the relationship between Aβ deposition and brain structure, as determined using 11C-Pittsburgh compound B (PiB) and magnetic resonance imaging (MRI), respectively, we developed a [...] Read more.
The neuropathological diagnosis of Alzheimer’s disease (AD) relies on amyloid beta (Aβ) deposition in brain tissues. To study the relationship between Aβ deposition and brain structure, as determined using 11C-Pittsburgh compound B (PiB) and magnetic resonance imaging (MRI), respectively, we developed a regression model with PiB and MRI data as the predictor and response variables, respectively, and proposed a regression method for studying the association between them based on a supervised sparse multivariate analysis with dimension reduction based on a composite paired basis function. By applying this method to imaging data of 61 patients with AD (age: 55–85), the first component showed the strongest correlation with the composite score, owing to the supervised feature. The spatial pattern included the hippocampal and parahippocampal regions for MRI. The peak value was observed in the posterior cingulate and precuneus for PiB. The differences in PiB scores among the diagnosis groups 12 months after PiB imaging were significant between the normal and AD groups (p = 0.0284), but not between the normal and mild cognitive impairment (MCI) groups or the MCI and AD groups (p = 0.3508). Our method may facilitate the development of a dementia biomarker from brain imaging data. Scoring imaging data allows for visualization and the application of traditional analysis, facilitating clinical analysis for better interpretation of results. Full article
(This article belongs to the Special Issue Advances in Brain Magnetic Resonance Imaging)
►▼ Show Figures

Graphical abstract

13 pages, 5483 KiB  
Article
Using the Probability Density Function-Based Channel-Combination Bloch–Siegert Method Realizes Permittivity Imaging at 3T
by Jiajia Wang, Yunyu Gao and Sherman Xuegang Xin
Bioengineering 2024, 11(7), 699; https://doi.org/10.3390/bioengineering11070699 - 10 Jul 2024
Viewed by 1035
Abstract
Magnetic resonance electrical properties tomography (MR EPT) can retrieve permittivity from the B1+ magnitude. However, the accuracy of the permittivity measurement using MR EPT is still not ideal due to the low signal-to-noise ratio (SNR) of B1+ magnitude. In [...] Read more.
Magnetic resonance electrical properties tomography (MR EPT) can retrieve permittivity from the B1+ magnitude. However, the accuracy of the permittivity measurement using MR EPT is still not ideal due to the low signal-to-noise ratio (SNR) of B1+ magnitude. In this study, the probability density function (PDF)-based channel-combination Bloch–Siegert (BSS) method was firstly introduced to MR EPT for improving the accuracy of the permittivity measurement. MRI experiments were performed using a 3T scanner with an eight-channel receiver coil. The homogeneous water phantom was scanned for assessing the spatial distribution of B1+ magnitude obtained from the PDF-based channel-combination BSS method. Gadolinium (Gd) phantom and rats were scanned for assessing the feasibility of the PDF-based channel-combination BSS method in MR EPT. The Helmholtz-based EPT reconstruction algorithm was selected. For quantitative comparison, the permittivity measured by the open-ended coaxial probe method was considered as the ground-truth value. The accuracy of the permittivity measurement was estimated by the relative error between the reconstructed value and the ground-truth value. The reconstructed relative permittivity of Gd phantom was 52.413, while that of rat leg muscle was 54.053. The ground-truth values of relative permittivity of Gd phantom and rat leg muscle were 78.86 and 49.04, respectively. The relative error of average permittivity was 33.53% for Gd and 10.22% for rat leg muscle. The results indicated the high accuracy of the permittivity measurement using the PDF-based channel-combination BSS method in MR EPT. This improvement may promote the clinical application of MR EPT technology, such as in the early diagnosis of cancers. Full article
(This article belongs to the Special Issue Advances in Brain Magnetic Resonance Imaging)
►▼ Show Figures

Graphical abstract

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop