AIMC Topic: Neural Networks, Computer

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A Transfer-Learning Approach for Accelerated MRI Using Deep Neural Networks.

Magnetic resonance in medicine
PURPOSE: Neural networks have received recent interest for reconstruction of undersampled MR acquisitions. Ideally, network performance should be optimized by drawing the training and testing data from the same domain. In practice, however, large dat...

A Two-Stage Convolutional Neural Networks for Lung Nodule Detection.

IEEE journal of biomedical and health informatics
Early detection of lung cancer is an effective way to improve the survival rate of patients. It is a critical step to have accurate detection of lung nodules in computed tomography (CT) images for the diagnosis of lung cancer. However, due to the het...

Automated volumetric assessment with artificial neural networks might enable a more accurate assessment of disease burden in patients with multiple sclerosis.

European radiology
OBJECTIVES: Patients with multiple sclerosis (MS) regularly undergo MRI for assessment of disease burden. However, interpretation may be time consuming and prone to intra- and interobserver variability. Here, we evaluate the potential of artificial n...

Super-resolution of cardiac magnetic resonance images using Laplacian Pyramid based on Generative Adversarial Networks.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
BACKGROUND AND OBJECTIVE: Cardiac magnetic resonance imaging (MRI) can assist in both functional and structural analysis of the heart, but due to hardware and physical limitations, high-resolution MRI scans is time consuming and peak signal-to-noise ...

Graph Convolutional Neural Networks as "General-Purpose" Property Predictors: The Universality and Limits of Applicability.

Journal of chemical information and modeling
Nowadays the development of new functional materials/chemical compounds using machine learning (ML) techniques is a hot topic and includes several crucial steps, one of which is the choice of chemical structure representation. The classical approach ...

De novo generation of hit-like molecules from gene expression signatures using artificial intelligence.

Nature communications
Finding new molecules with a desired biological activity is an extremely difficult task. In this context, artificial intelligence and generative models have been used for molecular de novo design and compound optimization. Herein, we report a generat...

Recognizing Image Semantic Information Through Multi-Feature Fusion and SSAE-Based Deep Network.

Journal of medical systems
Images are powerful tools with which to convey human emotions, with different images stimulating diverse emotions. Numerous factors affect the emotions stimulated by the image, and many researchers have previously focused on low-level features such a...

Forecasting stock prices with long-short term memory neural network based on attention mechanism.

PloS one
The stock market is known for its extreme complexity and volatility, and people are always looking for an accurate and effective way to guide stock trading. Long short-term memory (LSTM) neural networks are developed by recurrent neural networks (RNN...

Localization of common carotid artery transverse section in B-mode ultrasound images using faster RCNN: a deep learning approach.

Medical & biological engineering & computing
Cardiologists can acquire important information related to patients' cardiac health using carotid artery stiffness, its lumen diameter (LD), and its carotid intima-media thickness (cIMT). The sonographers primarily concern about the location of the a...