AIMC Topic: Brain

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Development of Gestational Age-Based Fetal Brain and Intracranial Volume Reference Norms Using Deep Learning.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Fetal brain MR imaging interpretations are subjective and require subspecialty expertise. We aimed to develop a deep learning algorithm for automatically measuring intracranial and brain volumes of fetal brain MRIs across gest...

CAN: Context-assisted full Attention Network for brain tissue segmentation.

Medical image analysis
Brain tissue segmentation is of great value in diagnosing brain disorders. Three-dimensional (3D) and two-dimensional (2D) segmentation methods for brain Magnetic Resonance Imaging (MRI) suffer from high time complexity and low segmentation accuracy,...

A dense residual U-net for multiple sclerosis lesions segmentation from multi-sequence 3D MR images.

International journal of medical informatics
Multiple Sclerosis (MS) is an autoimmune disease that causes brain and spinal cord lesions, which magnetic resonance imaging (MRI) can detect and characterize. Recently, deep learning methods have achieved remarkable results in the automated segmenta...

Automatic lesion detection and segmentation in F-flutemetamol positron emission tomography images using deep learning.

Biomedical engineering online
BACKGROUND: Beta amyloid in the brain, which was originally confirmed by post-mortem examinations, can now be confirmed in living patients using amyloid positron emission tomography (PET) tracers, and the accuracy of diagnosis can be improved by beta...

Deep learning-based Accelerated and Noise-Suppressed Estimation (DANSE) of quantitative Gradient-Recalled Echo (qGRE) magnetic resonance imaging metrics associated with human brain neuronal structure and hemodynamic properties.

NMR in biomedicine
The purpose of the current study was to introduce a Deep learning-based Accelerated and Noise-Suppressed Estimation (DANSE) method for reconstructing quantitative maps of biological tissue cellular-specific, R2t*, and hemodynamic-specific, R2', metri...

Population codes enable learning from few examples by shaping inductive bias.

eLife
Learning from a limited number of experiences requires suitable inductive biases. To identify how inductive biases are implemented in and shaped by neural codes, we analyze sample-efficient learning of arbitrary stimulus-response maps from arbitrary ...

An Artificial Intelligence Tool for Clinical Decision Support and Protocol Selection for Brain MRI.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Protocolling, the process of determining the most appropriate acquisition parameters for an imaging study, is time-consuming and produces variable results depending on the performing physician. The purpose of this study was to...

Sleep-like unsupervised replay reduces catastrophic forgetting in artificial neural networks.

Nature communications
Artificial neural networks are known to suffer from catastrophic forgetting: when learning multiple tasks sequentially, they perform well on the most recent task at the expense of previously learned tasks. In the brain, sleep is known to play an impo...

Minimizing the effect of white matter lesions on deep learning based tissue segmentation for brain volumetry.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Automated methods for segmentation-based brain volumetry may be confounded by the presence of white matter (WM) lesions, which introduce abnormal intensities that can alter the classification of not only neighboring but also distant brain tissue. The...

Multi-layer perceptron classification & quantification of neuronal survival in hypoxic-ischemic brain image slices using a novel gradient direction, grey level co-occurrence matrix image training.

PloS one
Hypoxic ischemic encephalopathy (HIE) is a major global cause of neonatal death and lifelong disability. Large animal translational studies of hypoxic ischemic brain injury, such as those conducted in fetal sheep, have and continue to play a key role...