AIMC Topic: Imaging, Three-Dimensional

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Endoflip vs high-definition manometry in the assessment of fecal incontinence: A data-driven unsupervised comparison.

Neurogastroenterology and motility
BACKGROUND: How much anal sphincter dysfunction contributes to fecal incontinence (FI) is not clear. High-definition anorectal manometry (HDAM) and functional luminal imaging probe (Endoflip) are two new techniques to study anal sphincter function.

Developing Noise-Resistant Three-Dimensional Single Particle Tracking Using Deep Neural Networks.

Analytical chemistry
Three-dimensional single particle tracking (3D SPT) is a powerful tool in various chemical and biological studies. In 3D SPT, z sensitive point spread functions (PSFs) are frequently used to generate different patterns, from which the axial position ...

Iterative multi-path tracking for video and volume segmentation with sparse point supervision.

Medical image analysis
Recent machine learning strategies for segmentation tasks have shown great ability when trained on large pixel-wise annotated image datasets. It remains a major challenge however to aggregate such datasets, as the time and monetary cost associated wi...

Convolutional Neural Network Using a Breast MRI Tumor Dataset Can Predict Oncotype Dx Recurrence Score.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Oncotype Dx is a validated genetic analysis that provides a recurrence score (RS) to quantitatively predict outcomes in patients who meet the criteria of estrogen receptor positive / human epidermal growth factor receptor-2 negative (ER+/...

Real-time microrobot posture recognition via biplane X-ray imaging system for external electromagnetic actuation.

International journal of computer assisted radiology and surgery
PURPOSE: As a promising intravascular therapeutic approach for autonomous catheterization, especially for thrombosis treatment, a microrobot or robotic catheter driven by an external electromagnetic actuation system has been recently investigated. Ho...

Automated dendritic spine detection using convolutional neural networks on maximum intensity projected microscopic volumes.

Journal of neuroscience methods
BACKGROUND: Dendritic spines are structural correlates of excitatory synapses in the brain. Their density and structure are shaped by experience, pointing to their role in memory encoding. Dendritic spine imaging, followed by manual analysis, is a pr...

Identifying epidermal growth factor receptor mutation status in patients with lung adenocarcinoma by three-dimensional convolutional neural networks.

The British journal of radiology
OBJECTIVE:: Genetic phenotype plays a central role in making treatment decisions of lung adenocarcinoma, especially the tyrosine-kinase-inhibitors-sensitive mutations of the epidermal growth factor receptor (EGFR) gene. We constructed three-dimension...

Automated deep-neural-network surveillance of cranial images for acute neurologic events.

Nature medicine
Rapid diagnosis and treatment of acute neurological illnesses such as stroke, hemorrhage, and hydrocephalus are critical to achieving positive outcomes and preserving neurologic function-'time is brain'. Although these disorders are often recognizabl...

Deep dense multi-path neural network for prostate segmentation in magnetic resonance imaging.

International journal of computer assisted radiology and surgery
PURPOSE: We propose an approach of 3D convolutional neural network to segment the prostate in MR images.

Improved perfusion pattern score association with type 2 diabetes severity using machine learning pipeline: Pilot study.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Type 2 diabetes mellitus (T2DM) is associated with alterations in the blood-brain barrier, neuronal damage, and arterial stiffness, thus affecting cerebral metabolism and perfusion. There is a need to implement machine-learning methodolog...