AIMC Topic: X-Rays

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Pneumonia Detection in Chest X-Ray Images Using Enhanced Restricted Boltzmann Machine.

Journal of healthcare engineering
The process of pneumonia detection has been the focus of researchers as it has proved itself to be one of the most dangerous and life-threatening disorders. In recent years, many machine learning and deep learning algorithms have been applied in an a...

Masked Joint Bilateral Filtering via Deep Image Prior for Digital X-Ray Image Denoising.

IEEE journal of biomedical and health informatics
Medical image denoising faces great challenges. Although deep learning methods have shown great potential, their efficiency is severely affected by millions of trainable parameters. The non-linearity of neural networks also makes them difficult to be...

Multiclass Classification for Detection of COVID-19 Infection in Chest X-Rays Using CNN.

Computational intelligence and neuroscience
Coronavirus took the world by surprise and caused a lot of trouble in all the important fields in life. The complexity of dealing with coronavirus lies in the fact that it is highly infectious and is a novel virus which is hard to detect with exact p...

BRAX, Brazilian labeled chest x-ray dataset.

Scientific data
Chest radiographs allow for the meticulous examination of a patient's chest but demands specialized training for proper interpretation. Automated analysis of medical imaging has become increasingly accessible with the advent of machine learning (ML) ...

DAFLNet: Dual Asymmetric Feature Learning Network for COVID-19 Disease Diagnosis in X-Rays.

Computational and mathematical methods in medicine
COVID-19 has become the largest public health event worldwide since its outbreak, and early detection is a prerequisite for effective treatment. Chest X-ray images have become an important basis for screening and monitoring the disease, and deep lear...

DCNN-FuzzyWOA: Artificial Intelligence Solution for Automatic Detection of COVID-19 Using X-Ray Images.

Computational intelligence and neuroscience
Artificial intelligence (AI) techniques have been considered effective technologies in diagnosing and breaking the transmission chain of COVID-19 disease. Recent research uses the deep convolution neural network (DCNN) as the discoverer or classifier...

Development of a Spine X-Ray-Based Fracture Prediction Model Using a Deep Learning Algorithm.

Endocrinology and metabolism (Seoul, Korea)
BACKGRUOUND: Since image-based fracture prediction models using deep learning are lacking, we aimed to develop an X-ray-based fracture prediction model using deep learning with longitudinal data.

Controlled Formation of Conduction Channels in Memristive Devices Observed by X-ray Multimodal Imaging.

Advanced materials (Deerfield Beach, Fla.)
Neuromorphic computing provides a means for achieving faster and more energy efficient computations than conventional digital computers for artificial intelligence (AI). However, its current accuracy is generally less than the dominant software-based...

ImageGCN: Multi-Relational Image Graph Convolutional Networks for Disease Identification With Chest X-Rays.

IEEE transactions on medical imaging
Image representation is a fundamental task in computer vision. However, most of the existing approaches for image representation ignore the relations between images and consider each input image independently. Intuitively, relations between images ca...

Detecting COVID-19 patients via MLES-Net deep learning models from X-Ray images.

BMC medical imaging
BACKGROUND: Corona Virus Disease 2019 (COVID-19) first appeared in December 2019, and spread rapidly around the world. COVID-19 is a pneumonia caused by novel coronavirus infection in 2019. COVID-19 is highly infectious and transmissible. By 7 May 20...