AIMC Topic: Imaging, Three-Dimensional

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DeepAlign, a 3D alignment method based on regionalized deep learning for Cryo-EM.

Journal of structural biology
Cryo Electron Microscopy (Cryo-EM) is currently one of the main tools to reveal the structural information of biological specimens at high resolution. Despite the great development of the techniques involved to solve the biological structures with Cr...

External validation of automated focal cortical dysplasia detection using morphometric analysis.

Epilepsia
OBJECTIVE: Focal cortical dysplasias (FCDs) are a common cause of drug-resistant focal epilepsy but frequently remain undetected by conventional magnetic resonance imaging (MRI) assessment. The visual detection can be facilitated by morphometric anal...

A Myocardial Segmentation Method Based on Adversarial Learning.

BioMed research international
Congenital heart defects (CHD) are structural imperfections of the heart or large blood vessels that are detected around birth and their symptoms vary wildly, with mild case patients having no obvious symptoms and serious cases being potentially life...

Value of 3D preoperative planning for primary total hip arthroplasty based on artificial intelligence technology.

Journal of orthopaedic surgery and research
BACKGROUND: Accurate preoperative planning is an important step for accurate reconstruction in total hip arthroplasty (THA). Presently, preoperative planning is completed using either a two-dimensional (2D) template or three-dimensional (3D) mimics s...

Reducing Contrast Agent Dose in Cardiovascular MR Angiography with Deep Learning.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Contrast-enhanced magnetic resonance angiography (MRA) is used to assess various cardiovascular conditions. However, gadolinium-based contrast agents (GBCAs) carry a risk of dose-related adverse effects.

Super-resolution head and neck MRA using deep machine learning.

Magnetic resonance in medicine
PURPOSE: To probe the feasibility of deep learning-based super-resolution (SR) reconstruction applied to nonenhanced MR angiography (MRA) of the head and neck.

Rapid 3D phenotypic analysis of neurons and organoids using data-driven cell segmentation-free machine learning.

PLoS computational biology
Phenotypic profiling of large three-dimensional microscopy data sets has not been widely adopted due to the challenges posed by cell segmentation and feature selection. The computational demands of automated processing further limit analysis of hard-...

Automatic segmentation and location learning of neonatal cerebral ventricles in 3D ultrasound data combining CNN and CPPN.

Computers in biology and medicine
Preterm neonates are highly likely to suffer from ventriculomegaly, a dilation of the Cerebral Ventricular System (CVS). This condition can develop into life-threatening hydrocephalus and is correlated with future neuro-developmental impairments. Con...

Deep learning-based X-ray inpainting for improving spinal 2D-3D registration.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Two-dimensional (2D)-3D registration is challenging in the presence of implant projections on intraoperative images, which can limit the registration capture range. Here, we investigate the use of deep-learning-based inpainting for removi...

A 3D densely connected convolution neural network with connection-wise attention mechanism for Alzheimer's disease classification.

Magnetic resonance imaging
PURPOSE: Alzheimer's disease (AD) is a progressive and irreversible neurodegenerative disease. In recent years, machine learning methods have been widely used on analysis of neuroimage for quantitative evaluation and computer-aided diagnosis of AD or...