An efficient explicit numerical scheme for diffusion-type equations with a highly inhomogeneous and highly anisotropic diffusion tensor

2007 ◽  
Vol 223 (1) ◽  
pp. 436-450 ◽  
Author(s):  
O. Larroche
Keyword(s):  
Anisotropic Diffusion ◽  
Numerical Scheme ◽  
Diffusion Tensor ◽  
Diffusion Type

scholarly journals A GENERALIZED DIFFUSION TENSOR FOR FULLY ANISOTROPIC DIFFUSION OF ENERGETIC PARTICLES IN THE HELIOSPHERIC MAGNETIC FIELD

2012 ◽  
Vol 750 (2) ◽  
pp. 108 ◽  
Author(s):  
F. Effenberger ◽  
H. Fichtner ◽  
K. Scherer ◽  
S. Barra ◽  
J. Kleimann ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Anisotropic Diffusion ◽  
Diffusion Tensor ◽  
Energetic Particles ◽  
Heliospheric Magnetic Field

DT-MRI of Central Nervous System: Clinical Applications

CNS Spectrums ◽  
2002 ◽  
Vol 7 (7) ◽  
pp. 535-542
Author(s):  
Xiaoming Li ◽  
Xavier Leclerc ◽  
Thierry Huisman ◽  
A. Gregory Sorensen
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
White Matter ◽  
Anisotropic Diffusion ◽  
Diffusion Tensor ◽  
Translational Motion ◽  
Clinical Effectiveness ◽  
Clinical Neurology ◽  
Acute Cerebral Ischemia ◽  
Tissue Characteristics

ABSTRACTDiffusion-weighted imaging (DWI) represents a relatively novel magnetic resonance imaging (MRI) technique in which image contrast is related to differences in translational motion of water molecules within the tissue, rather than to differences in total water content. The rate of water motion is characterized by the apparent diffusion coefficient. In addition, full tensor DWI (diffusion tensor imaging, DT-MRI) samples the full diffusion tensor and therefore allows estimation of isotropic and anisotropic diffusion. The degree of anisotropic diffusion is thought to be determined by the local tissue characteristics or tissue architecture and can be quantified by DT-MRI. DWI has proven its clinical effectiveness in the early detection of acute cerebral ischemia. Multiple reports have discussed the value of DWI in a wide variety of other diseases of the central nervous system. DT-MRI appears to be especially promising in the evaluation of diseases that affect the integrity of white matter, in particular of white matter tracts. Herein, the current applications of DWI in clinical neurology are reviewed, with special attention to applications of DT-MRI.

The Corpus Callosum in Monozygotic Twins Concordant and Discordant for Handedness and Language Dominance

2012 ◽  
Vol 24 (10) ◽  
pp. 1971-1982 ◽  
Author(s):  
Isabelle S. Häberling ◽  
Gjurgjica Badzakova-Trajkov ◽  
Michael C. Corballis
Keyword(s):  
Corpus Callosum ◽  
Anisotropic Diffusion ◽  
High Probability ◽  
Diffusion Tensor ◽  
Monozygotic Twins ◽  
Hemispheric Dominance ◽  
Connectivity Pattern ◽  
Language Dominance ◽  
Controlled Processes ◽  
High Connectivity

We used diffusion tensor imaging to assess callosal morphology in 35 pairs of monozygotic twins, of which 17 pairs were concordant for handedness and 18 pairs were discordant for handedness. Functional hemispheric language dominance was established for each twin member using fMRI, resulting in 26 twin pairs concordant and 9 twin pairs discordant for language dominance. On the basis of genetic models of handedness and language dominance, which assume one “right shift” (RS) gene with two alleles, an RS+ allele biasing toward right-handedness and left cerebral language dominance and an RS− allele leaving both asymmetries to chance, all twins were classified according to their putative genotypes, and the possible effects of the gene on callosal morphology was assessed. Whereas callosal size was under a high genetic control that was independent of handedness and language dominance, twin pairs with a high probability of carrying the putative RS+ allele showed a connectivity pattern characterized by a genetically controlled, low anisotropic diffusion over the whole corpus callosum. In contrast, the high connectivity pattern exhibited by twin pairs more likely to lack the RS+ allele was under significantly less genetic influence. The data suggest that handedness and hemispheric dominance for speech production might be at least partly dependent on genetically controlled processes of axonal pruning in the corpus callosum.

scholarly journals NUMERICAL ANALYSIS OF WAVE AND NEARSHORE CURRENT FIELDS AROUND LOW-CRESTED PERMEABLE DETACHED BREAKWATERS

2012 ◽  
Vol 1 (33) ◽  
pp. 80
Author(s):  
Takeshi Nishihata ◽  
Yoshimitsu Tajima ◽  
Shinji Sato
Keyword(s):  
Anisotropic Diffusion ◽  
Good Accuracy ◽  
Friction Model ◽  
Diffusion Type ◽  
Reflection And Transmission ◽  
Turbulent Friction ◽  
Wave Fields ◽  
Friction Term ◽  
Wave Breaking Model ◽  
Transmission Capability

A Boussinesq type numerical model was developed which can simulate both wave fields and current fields around permeable detached breakwaters. The validity of the model was verified through measurements of waves and nearshore currents in hydraulic experiments investigating reflection and transmission capability. The porosity of the structure was accounted by a friction term incorporating turbulent resistance. The combination of turbulent friction model and anisotropic diffusion type wave breaking model was found to reproduce wave fields around the detached breakwaters and nearshore current fields behind the structures with a good accuracy.

scholarly journals The role of diffusion tensor imaging metrics in machine learning-based characterisation of paediatric brain tumors and their practicality for multicentre clinical assessment

2021 ◽  
Vol 23 (Supplement_4) ◽  
pp. iv1-iv2
Author(s):  
Heather Rose ◽  
Huijun Li ◽  
Christopher D Bennett ◽  
Jan Novak ◽  
Yu Sun ◽  
...  
Keyword(s):  
Machine Learning ◽  
Brain Tumours ◽  
Anisotropic Diffusion ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
Imaging Biomarkers ◽  
Significant Difference ◽  
Mri Scans ◽  
Leave One Out ◽  
Paediatric Brain Tumours

Abstract Aims Magnetic resonance imaging (MRI) is a valuable tool for non-invasive diagnosis of paediatric brain tumours. The rarity of the disease dictates multi-centre studies and imaging biomarkers that are robust to protocol variability. We investigated diffusion tensor MRI (DT-MRI), combined with machine learning, as an aid to diagnosis and evaluated the robustness of the imaging metrics. Method A multi-centre cohort of 52 clinical DT-MRI scans (20 medulloblastomas (MB), 21 pilocytic astrocytomas (PA), 11 ependymomas (EP)) were analysed retrospectively. Histograms for regions of solid tumour for fractional anisotropy (FA), mean diffusivity (MD), pure anisotropic diffusion (q) and pure isotropic diffusion (p) were compared to assess diagnostic capability. Linear discriminate analysis (LDA) was used for classification and validated using leave-one-out-cross-validation (LOOCV). Results Histogram medians for FA, MD, q and p were all different between tumor groups (P<.0001, Kruskal Wallis test). Median MD, p and q values were highest in PA, then EP and lowest in MB (P<.0001, Pairwise Wilcox test). FA median was higher for EP than PA (P=.004) with no significant difference between EP and MB (P=.591). ROC analysis showed that median MD, q and p perform best as a diagnostic marker (AUC= 0.92 to 0.99). LOOCV showed an overall accuracy of the LDA classification, ranging between 67% - 87%. FA values were highly dependent on protocol parameters, whereas pure anisotropic diffusion, q, was not. Conclusion DT-MRI metrics from multi-centre acquisitions can classify paediatric brain tumours. FA is the least robust metric to protocol variability and q provides the most robust quantification of anisotropic behaviour.

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