AIMC Topic: Neural Networks, Computer

Clear Filters Showing 8821 to 8830 of 31376 articles

Neuromorphic applications in medicine.

Journal of neural engineering
In recent years, there has been a growing demand for miniaturization, low power consumption, quick treatments, and non-invasive clinical strategies in the healthcare industry. To meet these demands, healthcare professionals are seeking new technologi...

OCIF: automatically learning the optimized clinical information fusion method for computer-aided diagnosis tasks.

International journal of computer assisted radiology and surgery
PURPOSE: In computer-aided diagnosis, the fusion of image features extracted from neural networks and clinical information is crucial to improve diagnostic accuracy. How to integrate low-dimensional clinical information (LDCF) with high-dimensional n...

Adversarial attacks and defenses using feature-space stochasticity.

Neural networks : the official journal of the International Neural Network Society
Recent studies in deep neural networks have shown that injecting random noise in the input layer of the networks contributes towards ℓ-norm-bounded adversarial perturbations. However, to defend against unrestricted adversarial examples, most of which...

Feature-aware unsupervised lesion segmentation for brain tumor images using fast data density functional transform.

Scientific reports
We demonstrate that isomorphically mapping gray-level medical image matrices onto energy spaces underlying the framework of fast data density functional transform (fDDFT) can achieve the unsupervised recognition of lesion morphology. By introducing t...

Learning ADC maps from accelerated radial k-space diffusion-weighted MRI in mice using a deep CNN-transformer model.

Magnetic resonance in medicine
PURPOSE: To accelerate radially sampled diffusion weighted spin-echo (Rad-DW-SE) acquisition method for generating high quality ADC maps.

A multilayered bidirectional associative memory model for learning nonlinear tasks.

Neural networks : the official journal of the International Neural Network Society
A multilayered bidirectional associative memory neural network is proposed to account for learning nonlinear types of association. The model (denoted as the MF-BAM) is composed of two modules, the Multi-Feature extracting bidirectional associative me...

A Deep Regression Approach for Human Activity Recognition Under Partial Occlusion.

International journal of neural systems
In real-life scenarios, Human Activity Recognition (HAR) from video data is prone to occlusion of one or more body parts of the human subjects involved. Although it is common sense that the recognition of the majority of activities strongly depends o...

Fully automatic deep learning-based lung parenchyma segmentation and boundary correction in thoracic CT scans.

International journal of computer assisted radiology and surgery
PURPOSE: The proposed work aims to develop an algorithm to precisely segment the lung parenchyma in thoracic CT scans. To achieve this goal, the proposed technique utilized a combination of deep learning and traditional image processing algorithms. T...

A novel feature-scrambling approach reveals the capacity of convolutional neural networks to learn spatial relations.

Neural networks : the official journal of the International Neural Network Society
Convolutional neural networks (CNNs) are one of the most successful computer vision systems to solve object recognition. Furthermore, CNNs have major applications in understanding the nature of visual representations in the human brain. Yet it remain...

Predicting the severity of postoperative scars using artificial intelligence based on images and clinical data.

Scientific reports
Evaluation of scar severity is crucial for determining proper treatment modalities; however, there is no gold standard for assessing scars. This study aimed to develop and evaluate an artificial intelligence model using images and clinical data to pr...