AIMC Topic: Neural Networks, Computer

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Dynamic MRI reconstruction with end-to-end motion-guided network.

Medical image analysis
Temporal correlation in dynamic magnetic resonance imaging (MRI), such as cardiac MRI, is informative and important to understand motion mechanisms of body regions. Modeling such information into the MRI reconstruction process produces temporally coh...

A deep learning framework for quality assessment and restoration in video endoscopy.

Medical image analysis
Endoscopy is a routine imaging technique used for both diagnosis and minimally invasive surgical treatment. Artifacts such as motion blur, bubbles, specular reflections, floating objects and pixel saturation impede the visual interpretation and the a...

Deep-Learning-Assisted multivariate curve resolution.

Journal of chromatography. A
Gas chromatography-mass spectrometry (GC-MS) is one of the major platforms for analyzing volatile compounds in complex samples. However, automatic and accurate extraction of qualitative and quantitative information is still challenging when analyzing...

A scoping review of transfer learning research on medical image analysis using ImageNet.

Computers in biology and medicine
OBJECTIVE: Employing transfer learning (TL) with convolutional neural networks (CNNs), well-trained on non-medical ImageNet dataset, has shown promising results for medical image analysis in recent years. We aimed to conduct a scoping review to ident...

Introduction to part two of the special issue on computational models of hippocampus and related structures.

Hippocampus
Extensive computational modeling has focused on the hippocampal formation and related cortical structures. This introduction describes the topics addressed by individual articles in part two of this special issue of the journal Hippocampus on the top...

Advancing Biosensors with Machine Learning.

ACS sensors
Chemometrics play a critical role in biosensors-based detection, analysis, and diagnosis. Nowadays, as a branch of artificial intelligence (AI), machine learning (ML) have achieved impressive advances. However, novel advanced ML methods, especially d...

A Benchmark of Data Stream Classification for Human Activity Recognition on Connected Objects.

Sensors (Basel, Switzerland)
This paper evaluates data stream classifiers from the perspective of connected devices, focusing on the use case of Human Activity Recognition. We measure both the classification performance and resource consumption (runtime, memory, and power) of fi...

Artificial intelligence for melanoma diagnosis.

Italian journal of dermatology and venereology
Convolutional neural networks (CNN) have shown unprecedented accuracy in digital image analysis, which can be harnessed for melanoma recognition through automated evaluation of clinical and dermatoscopic images. In experimental studies, modern CNN ar...

Leveraging machine learning for predicting human body model response in restraint design simulations.

Computer methods in biomechanics and biomedical engineering
The objective of this study was to leverage and compare multiple machine learning techniques for predicting the human body model response in restraint design simulations. Parametric simulations with 16 independent variables were performed. Ordinary l...

Ischemic Lesion Segmentation using Ensemble of Multi-Scale Region Aligned CNN.

Computer methods and programs in biomedicine
The first and foremost step in the diagnosis of ischemic stroke is the delineation of the lesion from radiological images for effective treatment planning. Manual delineation of the lesion by radiological experts is generally laborious and time-consu...