AIMC Topic: Neural Networks, Computer

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Artificial Neural Networks as a powerful numerical tool to classify specific features of a tooth based on 3D scan data.

Computers in biology and medicine
Chairside manufacturing based on digital image acquisition is gainingincreasing importance in dentistry. For the standardized application of these methods, it is paramount to have highly automated digital workflows that can process acquired 3D image ...

Automatic abdominal multi-organ segmentation using deep convolutional neural network and time-implicit level sets.

International journal of computer assisted radiology and surgery
PURPOSE: Multi-organ segmentation from CT images is an essential step for computer-aided diagnosis and surgery planning. However, manual delineation of the organs by radiologists is tedious, time-consuming and poorly reproducible. Therefore, we propo...

Building machines that learn and think like people.

The Behavioral and brain sciences
Recent progress in artificial intelligence has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and boa...

Micro-Doppler Based Classification of Human Aquatic Activities via Transfer Learning of Convolutional Neural Networks.

Sensors (Basel, Switzerland)
Accurate classification of human aquatic activities using radar has a variety of potential applications such as rescue operations and border patrols. Nevertheless, the classification of activities on using radar has not been extensively studied, unl...

Automatic 3D liver segmentation based on deep learning and globally optimized surface evolution.

Physics in medicine and biology
The detection and delineation of the liver from abdominal 3D computed tomography (CT) images are fundamental tasks in computer-assisted liver surgery planning. However, automatic and accurate segmentation, especially liver detection, remains challeng...

A simplified computational memory model from information processing.

Scientific reports
This paper is intended to propose a computational model for memory from the view of information processing. The model, called simplified memory information retrieval network (SMIRN), is a bi-modular hierarchical functional memory network by abstracti...

Real-Time Control of an Articulatory-Based Speech Synthesizer for Brain Computer Interfaces.

PLoS computational biology
Restoring natural speech in paralyzed and aphasic people could be achieved using a Brain-Computer Interface (BCI) controlling a speech synthesizer in real-time. To reach this goal, a prerequisite is to develop a speech synthesizer producing intelligi...

A Convolutional Neural Network for Automatic Characterization of Plaque Composition in Carotid Ultrasound.

IEEE journal of biomedical and health informatics
Characterization of carotid plaque composition, more specifically the amount of lipid core, fibrous tissue, and calcified tissue, is an important task for the identification of plaques that are prone to rupture, and thus for early risk estimation of ...

Predictors of in-hospital mortality following major lower extremity amputations in type 2 diabetic patients using artificial neural networks.

BMC medical research methodology
BACKGROUND: Outcome prediction is important in the clinical decision-making process. Artificial neural networks (ANN) have been used to predict the risk of post-operative events, including survival, and are increasingly being used in complex medical ...

Exponentially Long Orbits in Hopfield Neural Networks.

Neural computation
We show that Hopfield neural networks with synchronous dynamics and asymmetric weights admit stable orbits that form sequences of maximal length. For [Formula: see text] units, these sequences have length [Formula: see text]; that is, they cover the ...