Article
Engineering, Multidisciplinary
Aissam Hadri, Amine Laghrib, Idriss El Mourabit
Summary: In this paper, an improved enhancement space-variant anisotropic PDE-constrained method for image denoising is proposed based on a learning optimization procedure. The tensor structure of Weickert-type operators is utilized to encode three critical parameters, A1, A2, and 0, which define the local direction geometry and control the smoothing intensity. Automatic parameter estimation and a non-smooth ADMM algorithm are introduced for the numerical solution. Experimental results demonstrate the superiority of this new method over other denoising approaches in terms of visual and quantitative measures.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Radiology, Nuclear Medicine & Medical Imaging
Hai Lin, Zesi Liu, Wei Yan, Doudou Zhang, Jiali Liu, Bin Xu, Weiping Li, Qiusheng Zhang, Xiaodong Cai
Summary: This study investigated brain connectivity markers of MCI in PD patients using MRI techniques, identifying nine features significantly relevant to patient classification. These features, unique in PD patients, were successfully used to distinguish patients with and without MCI with an accuracy of 83.9% using a random forest model. The results suggest that structural and functional connectivity abnormalities may contribute to cognitive impairment in PD and facilitate predicting MCI diagnosis outcomes.
EUROPEAN RADIOLOGY
(2021)
Article
Computer Science, Artificial Intelligence
Guangyu Yang, Weibo Wei, Zhenkuan Pan
Summary: In this paper, three second-order anisotropic variational models utilizing directional Hessian are proposed. The models are decomposed into a set of simple sub-problems using the alternating direction method of multipliers (ADMM) algorithm, which improves computational efficiency. Experimental results demonstrate better performances of these models in image restoration.
JOURNAL OF MATHEMATICAL IMAGING AND VISION
(2023)
Article
Neurosciences
Marco Marino, Lucilio Cordero-Grande, Dante Mantini, Giulio Ferrazzi
Summary: A new method for conductivity tensor imaging independent of traditional approaches has been proposed, combining water concentration and diffusion tensor imaging data to improve the quality of conductivity maps with achieved spatial resolution. This method can be used for defining head tissue compartments and assessing pathological changes in the brain.
FRONTIERS IN NEUROSCIENCE
(2021)
Article
Clinical Neurology
Iftakher Hossain, Mehrbod Mohammadian, Henna-Riikka Maanpaeae, Riikka S. K. Takala, Olli Tenovuo, Mark van Gils, Peter Hutchinson, David K. Menon, Virginia F. Newcombe, Jussi Tallus, Jussi Hirvonen, Timo Roine, Timo Kurki, Kaj Blennow, Henrik Zetterberg, Jussi P. Posti
Summary: This study examines the association between plasma NF-L levels at admission and white matter integrity in post-acute stage DW-MRI in mTBI patients. The results suggest that early levels of plasma NF-L may be associated with the presence of diffuse axonal injury (DAI) in mTBI patients over a period of 3 months.
Article
Medicine, Research & Experimental
Boyu Chen, Ming Xu, Hongmei Yu, Jiachuan He, Yingmei Li, Dandan Song, Guo Guang Fan
Summary: This study aimed to automatically classify Parkinson's disease patients without dementia into mild cognitive impairment (PD-MCI) and normal cognition (PD-NC) groups using an expanded range of measurement indices in white matter areas and a machine learning model. The results showed that combining intra- and intervoxel indices can improve classification accuracy, providing a new method for automatic identification of PD-MCI at the individual level.
JOURNAL OF TRANSLATIONAL MEDICINE
(2023)
Article
Mathematical & Computational Biology
Jimin Yu, Jiajun Yin, Shangbo Zhou, Saiao Huang, Xianzhong Xie
Summary: A novel model based on improved diffusion equation is proposed in this paper to address the issues in image denoising and super-resolution reconstruction. By adapting coefficient calculation of fidelity term and introducing washout filter, the image quality and stability can be enhanced significantly. The experimental results demonstrate that the proposed algorithm effectively prevents the staircase effect and achieves better visual effect.
MATHEMATICAL BIOSCIENCES AND ENGINEERING
(2021)
Article
Geriatrics & Gerontology
Anna Behler, Jan Kassubek, Hans-Peter Mueller
Summary: The study found that diffusion metrics in the brain undergo nonlinear changes with age, exhibiting regional differences in brain anatomy. Age correction of diffusion properties should be considered for different white matter regions and age ranges, with three proposed approaches based on fiber tracking techniques.
FRONTIERS IN AGING NEUROSCIENCE
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Praitayini Kanakaraj, Leon Y. Cai, Francois Rheault, Fang-Cheng Yehe, Baxter P. Rogers, Kurt G. Schilling, Bennett A. Landman
Summary: In diffusion MRI, gradient nonlinearities can distort diffusion gradients, leading to biased diffusion tensor information. This study investigates the impact of gradient nonlinearity correction in the presence of noise. Empirical gradient nonlinear fields were introduced at different signal-to-noise ratio levels in tensor field and brain simulation experiments, and the effects were evaluated using diffusion metrics. The study suggests that gradient nonlinearity correction has more beneficial effects than adverse effects, and it is recommended for areas with pronounced nonlinearities.
MAGNETIC RESONANCE IMAGING
(2023)
Article
Neurosciences
Cirong Liu, Cecil Chern-Chyi Yen, Diego Szczupak, Xiaoguang Tian, Daniel Glen, Afonso C. Silva
Summary: The study introduces new population-based in-vivo standard templates and tools derived from multi-modal data of 27 marmosets, facilitating neuroimaging analysis and visualization. These templates and tools provide comprehensive support for common marmoset brain research.
Article
Clinical Neurology
Si-ping Luo, Fan-fan Chen, Han-wen Zhang, Fan Lin, Guo-dong Huang, Yi Lei
Summary: This study used DSI to quantitatively study the changes in the trigeminal cistern segment in patients with TN and found significant reductions in quantitative parameters on the affected side compared to the unaffected side. DSI, with its high-resolution fiber tracking technology, can provide valuable information about the integrity of trigeminal white matter in TN patients.
FRONTIERS IN NEUROLOGY
(2022)
Article
Computer Science, Interdisciplinary Applications
Juhyung Park, Woojin Jung, Eun-Jung Choi, Se-Hong Oh, Jinhee Jang, Dongmyung Shin, Hongjun An, Jongho Lee
Summary: This study developed a new deep neural network called DIFFnet as a generalized reconstruction tool for diffusion-weighted signals. DIFFnet showed accurate reconstruction capability for different gradient schemes and b-values, with significantly reduced processing time. The network's generalization capability was also validated.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2022)
Article
Engineering, Biomedical
Aliesha Danielle O'Raw, Nikolai Rakhilin, Nian Wang, Jennifer McKey, Gary Cofer, Robert B. J. Anderson, Blanche Capel, G. Allan Johnson, Xiling Shen
Summary: The study produced a comprehensive peripheral nerve atlas of the entire mouse PNS using diffusion tensor magnetic resonance imaging (DT-MRI) and high-speed compressed sensing techniques. The atlas mapped PNS innervation and fiber network in multiple organs at a resolution of 70 μm, providing unprecedented information on the neural circuitry throughout the body. This high-resolution nerve atlas could potentially guide future neuromodulation therapies and studies on neural circuits involved in homeostasis and disease.
JOURNAL OF NEURAL ENGINEERING
(2021)
Review
Clinical Neurology
Chengmin Yang, Li Yao, Naici Liu, Wenjing Zhang, Bo Tao, Hengyi Cao, Qiyong Gong, Su Lui
Summary: This study investigated white matter deficits in patients with TS, finding robustly decreased FA in the corpus callosum and right inferior longitudinal fasciculus compared with healthy controls. The results suggest important abnormalities in interhemispheric connections and long association fiber bundles in TS, with future research needed to support these findings with larger sample sizes.
FRONTIERS IN NEUROLOGY
(2021)
Article
Geochemistry & Geophysics
Jing Wang, Junhua Zhang, Yong Yang, Yushan Du
Summary: The algorithm developed for seismic data filtering preserves boundary information of faults and other geological bodies while suppressing noise by utilizing anisotropic diffusion filtering theory. It introduces stratigraphic coherence coefficients and fault confidence measures to control filtering intensity in different orientations, effectively suppressing noise, preserving faults, and enhancing reflector continuity. The results show high signal-to-noise ratio basic data for subsequent seismic interpretation.
GEOPHYSICAL PROSPECTING
(2021)