AIMC Topic: Brain

Clear Filters Showing 1491 to 1500 of 4413 articles

3D Ultrasonic Brain Imaging with Deep Learning Based on Fully Convolutional Networks.

Sensors (Basel, Switzerland)
Compared to magnetic resonance imaging (MRI) and X-ray computed tomography (CT), ultrasound imaging is safer, faster, and more widely applicable. However, the use of conventional ultrasound in transcranial brain imaging for adults is predominantly hi...

Bayesian learning from multi-way EEG feedback for robot navigation and target identification.

Scientific reports
Many brain-computer interfaces require a high mental workload. Recent research has shown that this could be greatly alleviated through machine learning, inferring user intentions via reactive brain responses. These signals are generated spontaneously...

Global and Regional Deep Learning Models for Multiple Sclerosis Stratification From MRI.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: The combination of anatomical MRI and deep learning-based methods such as convolutional neural networks (CNNs) is a promising strategy to build predictive models of multiple sclerosis (MS) prognosis. However, studies assessing the effect ...

Quantitative Electroencephalography Objectivity and Reliability in the Diagnosis and Management of Traumatic Brain Injury: A Systematic Review.

Clinical EEG and neuroscience
Persons with a history of traumatic brain injury (TBI) may exhibit short- and long-term cognitive deficits as well as psychiatric symptoms. These symptoms often reflect functional anomalies in the brain that are not detected by standard neuroimaging...

Iontronic Nanopore Model for Artificial Neurons: The Requisites of Spiking.

The journal of physical chemistry letters
Brain-inspired neuromorphic computing is currently being investigated for effective artificial intelligence (AI) systems. The development of artificial neurons and synapses is imperative to creating efficient computational biomimetic networks. Here w...

Natural variability in bee brain size and symmetry revealed by micro-CT imaging and deep learning.

PLoS computational biology
Analysing large numbers of brain samples can reveal minor, but statistically and biologically relevant variations in brain morphology that provide critical insights into animal behaviour, ecology and evolution. So far, however, such analyses have req...

A topological classifier to characterize brain states: When shape matters more than variance.

PloS one
Despite the remarkable accuracies attained by machine learning classifiers to separate complex datasets in a supervised fashion, most of their operation falls short to provide an informed intuition about the structure of data, and, what is more impor...

Deep learning-driven adaptive optics for single-molecule localization microscopy.

Nature methods
The inhomogeneous refractive indices of biological tissues blur and distort single-molecule emission patterns generating image artifacts and decreasing the achievable resolution of single-molecule localization microscopy (SMLM). Conventional sensorle...

D-LMBmap: a fully automated deep-learning pipeline for whole-brain profiling of neural circuitry.

Nature methods
Recent proliferation and integration of tissue-clearing methods and light-sheet fluorescence microscopy has created new opportunities to achieve mesoscale three-dimensional whole-brain connectivity mapping with exceptionally high throughput. With the...