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X-Rays

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COVID-19 classification using chest X-ray images: A framework of CNN-LSTM and improved max value moth flame optimization.

Frontiers in public health
Coronavirus disease 2019 (COVID-19) is a highly contagious disease that has claimed the lives of millions of people worldwide in the last 2 years. Because of the disease's rapid spread, it is critical to diagnose it at an early stage in order to redu...

CheXGAT: A disease correlation-aware network for thorax disease diagnosis from chest X-ray images.

Artificial intelligence in medicine
Chest X-ray (CXR) imaging is one of the most common diagnostic imaging techniques in clinical diagnosis and is usually used for radiological examinations to screen for thorax diseases. In this paper, we propose a novel computer-aided diagnosis (CAD) ...

Development of a computer-aided quality assurance support system for identifying hand X-ray image direction using deep convolutional neural network.

Radiological physics and technology
The convenience of imaging has improved with digitization; however, there has been no progress in the methods used to prevent human error. Therefore, radiographic incidents and accidents are not prevented. In Japan, image interpretation is conducted ...

Deep learning-based dental implant recognition using synthetic X-ray images.

Medical & biological engineering & computing
A novel algorithm for generating artificial training samples from triangulated three-dimensional (3D) surface models within the context of dental implant recognition is proposed. The proposed algorithm is based on the calculation of two-dimensional (...

Development of deep learning chest X-ray model for cardiac dose prediction in left-sided breast cancer radiotherapy.

Scientific reports
Deep inspiration breath-hold (DIBH) is widely used to reduce the cardiac dose in left-sided breast cancer radiotherapy. This study aimed to develop a deep learning chest X-ray model for cardiac dose prediction to select patients with a potentially hi...

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...