Quantitative susceptibility mapping reveals alterations of dentate nuclei in common types of degenerative cerebellar ataxias

A Deistung, D Jäschke, R Draganova… - Brain …, 2022 - academic.oup.com
The cerebellar nuclei are a brain region with high iron content. Surprisingly, little is known
about iron content in the cerebellar nuclei and its possible contribution to pathology in …

Automated segmentation of deep brain nuclei using convolutional neural networks and susceptibility weighted imaging

V Beliveau, M Nørgaard, C Birkl, K Seppi, C Scherfler - 2021 - Wiley Online Library
The advent of susceptibility‐sensitive MRI techniques, such as susceptibility weighted
imaging (SWI), has enabled accurate in vivo visualization and quantification of iron …

糖尿病肾病病理机制及治疗措施的研究进展

杨静, 傅继华 - 医学研究与教育, 2020 - yxyjyjy.hbu.edu.cn
糖尿病肾病是糖尿病中最常见的微血管并发症, 是一种慢性进行性肾脏疾病.
糖尿病肾病也是导致终末期肾病的主要原因之一. 为了更好地保护和预防糖尿病肾病的进展 …

Deep interpretability methods for neuroimaging

MM Rahman - 2022 - scholarworks.gsu.edu
Brain dynamics are highly complex and yet hold the key to understanding brain function and
dysfunction. The dynamics captured by resting-state functional magnetic resonance imaging …

Automatic segmentation of dentate nuclei for microstructure assessment: Example of application to temporal lobe epilepsy patients

M Gaviraghi, G Savini, G Castellazzi, F Palesi… - … MICCAI Workshop, Lima …, 2021 - Springer
Dentate nuclei (DNs) segmentation is helpful for assessing their potential involvement in
neurological diseases. Once DNs have been segmented, it becomes possible to investigate …

[PDF][PDF] BRAIN COMMUNICATIONS AIN COMMUNICATIONS

A Deistung, D Jäschke, R Draganova, V Pfaffenrot… - 2022 - juser.fz-juelich.de
Quantitative susceptibility mapping reveals alterations of dentate nuclei in common types of
degenerative cerebellar ataxias Page 1 Quantitative susceptibility mapping reveals …

Data-Driven Structural Neuroimaging Metrics to Quantify Aging and Cardiovascular Disease

C Bermudez Noguera - 2020 - ir.vanderbilt.edu
The amount of radiological imaging data being generated is growing at an unprecedented
pace. Concurrently, analytical tools in image processing and big data are making it feasible …