[HTML][HTML] A test-retest study on Parkinson's PPMI dataset yields statistically significant white matter fascicles
In this work, we propose a diffusion MRI protocol for mining Parkinson's disease diffusion
MRI datasets and recover robust disease-specific biomarkers. Using advanced high angular …
MRI datasets and recover robust disease-specific biomarkers. Using advanced high angular …
Unexpected (123I)FP-CIT SPECT findings: SWIDD, SWEDD and all DAT
Although the diagnosis of Parkinson's disease (PD) is essentially clinical, the
implementation of imaging techniques can improve diagnostic accuracy. While some …
implementation of imaging techniques can improve diagnostic accuracy. While some …
[HTML][HTML] Connectome analysis with diffusion MRI in idiopathic Parkinson's disease: Evaluation using multi-shell, multi-tissue, constrained spherical deconvolution
Parkinson's disease (PD) is a progressive neurodegenerative disorder that affects extensive
regions of the central nervous system. In this work, we evaluated the structural connectome …
regions of the central nervous system. In this work, we evaluated the structural connectome …
Novel effective connectivity inference using ultra-group constrained orthogonal forward regression and elastic multilayer perceptron classifier for MCI identification
Mild cognitive impairment (MCI) detection is important, such that appropriate interventions
can be imposed to delay or prevent its progression to severe stages, including Alzheimer's …
can be imposed to delay or prevent its progression to severe stages, including Alzheimer's …
Heterogeneous digital biomarker integration out-performs patient self-reports in predicting Parkinson's disease
Parkinson's disease (PD) is one of the first diseases where digital biomarkers demonstrated
excellent performance in differentiating disease from healthy individuals. However, no study …
excellent performance in differentiating disease from healthy individuals. However, no study …
TractGraphFormer: Anatomically Informed Hybrid Graph CNN-Transformer Network for Classification from Diffusion MRI Tractography
The relationship between brain connections and non-imaging phenotypes is increasingly
studied using deep neural networks. However, the local and global properties of the brain's …
studied using deep neural networks. However, the local and global properties of the brain's …
Feature engineering-based analysis of DaTSCAN-SPECT imaging-derived features in the detection of SWEDD and Parkinson's disease
Scans without evidence of dopamine deficit (SWEDD) refer to patients with a normal
dopamine transporter scan who have been clinically considered to have Parkinson's …
dopamine transporter scan who have been clinically considered to have Parkinson's …
A ReliefF-SVM-based method for marking dopamine-based disease characteristics: A study on SWEDD and Parkinson's disease
Parkinson's disease (PD) and scans without evidence of dopaminergic deficit (SWEDD) are
two distinct neurological disorders that require different therapeutic approaches; therefore …
two distinct neurological disorders that require different therapeutic approaches; therefore …
Alteration of diffusion-tensor magnetic resonance imaging measures in brain regions involved in early stages of parkinson's disease
Many nonmotor symptoms (eg, hyposmia) appear years before the cardinal motor features
of Parkinson's disease (PD). It is thus desirable to be able to use noninvasive brain imaging …
of Parkinson's disease (PD). It is thus desirable to be able to use noninvasive brain imaging …
A deep 1-D CNN learning approach with data augmentation for classification of Parkinson's disease and scans without evidence of dopamine deficit (SWEDD)
Abstract Objective Discriminating Parkinson's disease (PD) patients from the SWEDD cases
remains a major challenge. Basically, SWEDD cases show normal dopamine transporter …
remains a major challenge. Basically, SWEDD cases show normal dopamine transporter …