AI Medical Compendium Topic:
Neuroimaging

Clear Filters Showing 821 to 826 of 826 articles

Label-aligned multi-task feature learning for multimodal classification of Alzheimer's disease and mild cognitive impairment.

Brain imaging and behavior
Multimodal classification methods using different modalities of imaging and non-imaging data have recently shown great advantages over traditional single-modality-based ones for diagnosis and prognosis of Alzheimer's disease (AD), as well as its prod...

Learning-based subject-specific estimation of dynamic maps of cortical morphology at missing time points in longitudinal infant studies.

Human brain mapping
Longitudinal neuroimaging analysis of the dynamic brain development in infants has received increasing attention recently. Many studies expect a complete longitudinal dataset in order to accurately chart the brain developmental trajectories. However,...

Addressing Confounding in Predictive Models with an Application to Neuroimaging.

The international journal of biostatistics
Understanding structural changes in the brain that are caused by a particular disease is a major goal of neuroimaging research. Multivariate pattern analysis (MVPA) comprises a collection of tools that can be used to understand complex disease efxcfe...

A modified fuzzy C-means method for segmenting MR images using non-local information.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: In recent years, MR images have been increasingly used in therapeutic applications such as image-guided radiotherapy (IGRT). However, images with low contrast values and noises present challenges for image segmentation.

Using structural MRI to identify individuals at genetic risk for bipolar disorders: a 2-cohort, machine learning study.

Journal of psychiatry & neuroscience : JPN
BACKGROUND: Brain imaging is of limited diagnostic use in psychiatry owing to clinical heterogeneity and low sensitivity/specificity of between-group neuroimaging differences. Machine learning (ML) may better translate neuroimaging to the level of in...

Visual and somatic sensory feedback of brain activity for intuitive surgical robot manipulation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This paper presents a method to evaluate the hand-eye coordination of the master-slave surgical robot by measuring the activation of the intraparietal sulcus in users brain activity during controlling virtual manipulation. The objective is to examine...