AIMC Topic: Neural Networks, Computer

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MD-SGT: Multi-dilation spherical graph transformer for unsupervised medical image registration.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Deformable medical image registration is an essential preprocess step for several clinical applications. Even though the existing convolutional neural network and transformer based methods achieved the promising results, the limited long-range spatia...

Physics-informed neural networks (PINNs) for 4D hemodynamics prediction: An investigation of optimal framework based on vascular morphology.

Computers in biology and medicine
Hemodynamic parameters are of great significance in the clinical diagnosis and treatment of cardiovascular diseases. However, noninvasive, real-time and accurate acquisition of hemodynamics remains a challenge for current invasive detection and simul...

Comparison of visual quantities in untrained neural networks.

Cell reports
The ability to compare quantities of visual objects with two distinct measures, proportion and difference, is observed even in newborn animals. However, how this function originates in the brain, even before visual experience, remains unknown. Here, ...

Numerical and Clinical Evaluation of the Robustness of Open-source Networks for Parallel MR Imaging Reconstruction.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
PURPOSE: Deep neural networks (DNNs) for MRI reconstruction often require large datasets for training. Still, in clinical settings, the domains of datasets are diverse, and how robust DNNs are to domain differences between training and testing datase...

Deep learning-based segmentation of dental implants on cone-beam computed tomography images: A validation study.

Journal of dentistry
OBJECTIVES: To train and validate a cloud-based convolutional neural network (CNN) model for automated segmentation (AS) of dental implant and attached prosthetic crown on cone-beam computed tomography (CBCT) images.

Deep Learning-Based Child Handwritten Arabic Character Recognition and Handwriting Discrimination.

Sensors (Basel, Switzerland)
Handwritten Arabic character recognition has received increasing research interest in recent years. However, as of yet, the majority of the existing handwriting recognition systems have only focused on adult handwriting. In contrast, there have not b...

Improved delineation model of a standard 12-lead electrocardiogram based on a deep learning algorithm.

BMC medical informatics and decision making
BACKGROUND: Signal delineation of a standard 12-lead electrocardiogram (ECG) is a decisive step for retrieving complete information and extracting signal characteristics for each lead in cardiology clinical practice. However, it is arduous to manuall...

Annotated dataset for deep-learning-based bacterial colony detection.

Scientific data
Quantifying bacteria per unit mass or volume is a common task in various fields of microbiology (e.g., infectiology and food hygiene). Most bacteria can be grown on culture media. The unicellular bacteria reproduce by dividing into two cells, which i...

Automated localization and segmentation of cervical lymph nodes on contrast-enhanced CT using a 3D foveal fully convolutional neural network.

European radiology experimental
BACKGROUND: In the management of cancer patients, determination of TNM status is essential for treatment decision-making and therefore closely linked to clinical outcome and survival. Here, we developed a tool for automatic three-dimensional (3D) loc...

Memristive Neural Networks for Predicting Seizure Activity.

Sovremennye tekhnologii v meditsine
UNLABELLED: is to assess the possibilities of predicting epileptiform activity using the neuronal activity data recorded from the hippocampus and medial entorhinal cortex of mice with chronic epileptiform activity. To reach this goal, a deep artific...