AIMC Topic: Brain

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Deep learning-based reconstruction for three-dimensional volumetric brain MRI: a qualitative and quantitative assessment.

BMC medical imaging
BACKGROUND: To evaluate the performance of a deep learning reconstruction (DLR) based on Adaptive-Compressed sensing (CS)-Network for brain MRI and validate it in a clinical setting.

Modelling fourth-order hyperelasticity in soft solids using physics informed neural networks without labelled data.

Brain research bulletin
Mild traumatic brain injury can result from shear shock wave formation in the brain in the event of a head impact like in contact sports, road traffic accidents, etc. These highly nonlinear deformations are modelled by a fourth-order Landau hyperelas...

Ensemble network using oblique coronal MRI for Alzheimer's disease diagnosis.

NeuroImage
Alzheimer's disease (AD) is a primary degenerative brain disorder commonly found in the elderly, Mild cognitive impairment (MCI) can be considered a transitional stage from normal aging to Alzheimer's disease. Therefore, distinguishing between normal...

An ensemble approach using multidimensional convolutional neural networks in wavelet domain for schizophrenia classification from sMRI data.

Scientific reports
Schizophrenia is a complicated mental condition marked by disruptions in thought processes, perceptions, and emotional responses, which can cause severe impairment in everyday functioning. sMRI is a non-invasive neuroimaging technology that visualize...

Using machine learning to simultaneously quantify multiple cognitive components of episodic memory.

Nature communications
Why do we remember some events but forget others? Previous studies attempting to decode successful vs. unsuccessful brain states to investigate this question have met with limited success, potentially due, in part, to assessing episodic memory as a u...

Enhancing Schizophrenia Diagnosis Through Multi-View EEG Analysis: Integrating Raw Signals and Spectrograms in a Deep Learning Framework.

Clinical EEG and neuroscience
Schizophrenia is a chronic mental disorder marked by symptoms such as hallucinations, delusions, and cognitive impairments, which profoundly affect individuals' lives. Early detection is crucial for improving treatment outcomes, but the diagnostic p...

TCDE-Net: An unsupervised dual-encoder network for 3D brain medical image registration.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Medical image registration is a critical task in aligning medical images from different time points, modalities, or individuals, essential for accurate diagnosis and treatment planning. Despite significant progress in deep learning-based registration...

Deformable image registration with strategic integration pyramid framework for brain MRI.

Magnetic resonance imaging
Medical image registration plays a crucial role in medical imaging, with a wide range of clinical applications. In this context, brain MRI registration is commonly used in clinical practice for accurate diagnosis and treatment planning. In recent yea...

Radiomics-based MRI model to predict hypoperfusion in lacunar infarction.

Magnetic resonance imaging
BACKGROUND: Approximately 20-30 % of patients with acute ischemic stroke due to lacunar infarction experience early neurological deterioration (END) within the first three days after onset, leading to disability or more severe sequelae. Hemodynamic p...

An extragradient and noise-tuning adaptive iterative network for diffusion MRI-based microstructural estimation.

Medical image analysis
Diffusion MRI (dMRI) is a powerful technique for investigating tissue microstructure properties. However, advanced dMRI models are typically complex and nonlinear, requiring a large number of acquisitions in the q-space. Deep learning techniques, spe...