AIMC Topic: Magnetic Resonance Imaging

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Diagnosis of Alzheimer's Disease Using View-Aligned Hypergraph Learning with Incomplete Multi-modality Data.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Effectively utilizing incomplete multi-modality data for diagnosis of Alzheimer's disease (AD) is still an area of active research. Several multi-view learning methods have recently been developed to deal with missing data, with each view correspondi...

Predicting symptom severity in autism spectrum disorder based on cortical thickness measures in agglomerative data.

NeuroImage
Machine learning approaches have been widely used for the identification of neuropathology from neuroimaging data. However, these approaches require large samples and suffer from the challenges associated with multi-site, multi-protocol data. We prop...

Towards person-centered neuroimaging markers for resilience and vulnerability in Bipolar Disorder.

NeuroImage
Improved clinical care for Bipolar Disorder (BD) relies on the identification of diagnostic markers that can reliably detect disease-related signals in clinically heterogeneous populations. At the very least, diagnostic markers should be able to diff...

Effects of adaptation on numerosity decoding in the human brain.

NeuroImage
Psychophysical studies have shown that numerosity is a sensory attribute susceptible to adaptation. Neuroimaging studies have reported that, at least for relatively low numbers, numerosity can be accurately discriminated in the intra-parietal sulcus....

Single NMR image super-resolution based on extreme learning machine.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
INTRODUCTION: The performance limitation of MRI equipment and higher resolution demand of NMR images from radiologists have formed a strong contrast. Therefore, it is important to study the super resolution algorithm suitable for NMR images, using lo...

Believing androids - fMRI activation in the right temporo-parietal junction is modulated by ascribing intentions to non-human agents.

Social neuroscience
Attributing mind to interaction partners has been shown to increase the social relevance we ascribe to others' actions and to modulate the amount of attention dedicated to them. However, it remains unclear how the relationship between higher-order mi...

A Magnetic Resonance Compatible Soft Wearable Robotic Glove for Hand Rehabilitation and Brain Imaging.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
In this paper, we present the design, fabrication and evaluation of a soft wearable robotic glove, which can be used with functional Magnetic Resonance imaging (fMRI) during the hand rehabilitation and task specific training. The soft wearable roboti...

Multiclass Classification for the Differential Diagnosis on the ADHD Subtypes Using Recursive Feature Elimination and Hierarchical Extreme Learning Machine: Structural MRI Study.

PloS one
The classification of neuroimaging data for the diagnosis of certain brain diseases is one of the main research goals of the neuroscience and clinical communities. In this study, we performed multiclass classification using a hierarchical extreme lea...

Neural correlates of motor recovery after robot-assisted stroke rehabilitation: a case series study.

Neurocase
Robot-assisted bilateral arm therapy (RBAT) has shown promising results in stroke rehabilitation; however, connectivity mapping of the sensorimotor networks after RBAT remains unclear. We used fMRI before and after RBAT and a dose-matched control int...

Decoding post-stroke motor function from structural brain imaging.

NeuroImage. Clinical
Clinical research based on neuroimaging data has benefited from machine learning methods, which have the ability to provide individualized predictions and to account for the interaction among units of information in the brain. Application of machine ...