AIMC Topic: Neural Networks, Computer

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MAD-UNet: A deep U-shaped network combined with an attention mechanism for pancreas segmentation in CT images.

Medical physics
PURPOSE: Pancreas segmentation is a difficult task because of the high intrapatient variability in the shape, size, and location of the organ, as well as the low contrast and small footprint of the CT scan. At present, the U-Net model is likely to le...

A Framework of Combining Short-Term Spatial/Frequency Feature Extraction and Long-Term IndRNN for Activity Recognition.

Sensors (Basel, Switzerland)
Smartphone-sensors-based human activity recognition is attracting increasing interest due to the popularization of smartphones. It is a difficult long-range temporal recognition problem, especially with large intraclass distances such as carrying sma...

Deep learning model for classification and bioactivity prediction of essential oil-producing plants from Egypt.

Scientific reports
Reliance on deep learning techniques has become an important trend in several science domains including biological science, due to its proven efficiency in manipulating big data that are often characterized by their non-linear processes and complicat...

A Multifrequency Brain Network-Based Deep Learning Framework for Motor Imagery Decoding.

Neural plasticity
Motor imagery (MI) is an important part of brain-computer interface (BCI) research, which could decode the subject's intention and help remodel the neural system of stroke patients. Therefore, accurate decoding of electroencephalography- (EEG-) based...

Data classification based on fractional order gradient descent with momentum for RBF neural network.

Network (Bristol, England)
The weight-updating methods have played an important role in improving the performance of neural networks. To ameliorate the oscillating phenomenon in training radial basis function (RBF) neural network, a fractional order gradient descent with momen...

Artificial fly visual joint perception neural network inspired by multiple-regional collision detection.

Neural networks : the official journal of the International Neural Network Society
The biological visual system includes multiple types of motion sensitive neurons which preferentially respond to specific perceptual regions. However, it still keeps open how to borrow such neurons to construct bio-inspired computational models for m...

Current status of artificial intelligence analysis for endoscopic ultrasonography.

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
Endoscopic ultrasonography (EUS) is an essential diagnostic tool for various types of pancreatic diseases such as pancreatic tumors and chronic pancreatitis; however, EUS imaging has low specificity for the diagnosis of pancreatic diseases. Artificia...

Comparison of the suitability of CBCT- and MR-based synthetic CTs for daily adaptive proton therapy in head and neck patients.

Physics in medicine and biology
Cone-beam computed tomography (CBCT)- and magnetic resonance (MR)-images allow a daily observation of patient anatomy but are not directly suited for accurate proton dose calculations. This can be overcome by creating synthetic CTs (sCT) using deep c...

MD-NDNet: a multi-dimensional convolutional neural network for false-positive reduction in pulmonary nodule detection.

Physics in medicine and biology
Pulmonary nodule false-positive reduction is of great significance for automated nodule detection in clinical diagnosis of low-dose computed tomography (LDCT) lung cancer screening. Due to individual intra-nodule variations and visual similarities be...