AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

X-Rays

Showing 411 to 420 of 444 articles

Clear Filters

An Efficient Method for Coronavirus Detection Through X-rays Using Deep Neural Network.

Current medical imaging
BACKGROUND: Coronavirus (COVID-19) is a group of infectious diseases caused by related viruses called coronaviruses. In humans, the seriousness of infection caused by a coronavirus in the respiratory tract can vary from mild to lethal. A serious illn...

TDA-Net: Fusion of Persistent Homology and Deep Learning Features for COVID-19 Detection From Chest X-Ray Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Topological Data Analysis (TDA) has emerged recently as a robust tool to extract and compare the structure of datasets. TDA identifies features in data (e.g., connected components and holes) and assigns a quantitative measure to these features. Sever...

Deep Learning Framework for Automatic Bone Age Assessment.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Bone age Assessment or the skeletal age is a general clinical practice to detect endocrine and metabolic disarrangement in child development. The bone age indicates the level of structural and biological growth better than chronological age calculate...

Lung contour detection in Chest X-ray images using Mask Region-based Convolutional Neural Network and Adaptive Closed Polyline Searching Method.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Detection of lung contour on chest X-ray images (CXRs) is a necessary step for computer-aid medical imaging analysis. Because of the low-intensity contrast around lung boundary and large inter-subject variance, it is challenging to detect lung from s...

Deep Learning and Binary Relevance Classification of Multiple Diseases using Chest X-Ray images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Disease detection using chest X-ray (CXR) images is one of the most popular radiology methods to diagnose diseases through a visual inspection of abnormal symptoms in the lung region. A wide variety of diseases such as pneumonia, heart failure and lu...

Deep-Learning-Based Diagnosis of Bedside Chest X-ray in Intensive Care and Emergency Medicine.

Investigative radiology
OBJECTIVES: Validation of deep learning models should separately consider bedside chest radiographs (CXRs) as they are the most challenging to interpret, while at the same time the resulting diagnoses are important for managing critically ill patient...

[Automation of Damage Detection and Damage Area Measurement of X-ray Protective Clothing Using Deep Learning].

Nihon Hoshasen Gijutsu Gakkai zasshi
PURPOSE: Damage to shielding sheets on X-ray protective clothing may be a cause of increased radiation exposure. To prevent increased radiation exposure, periodic quality control of shielding sheets is needed. For quality management, a record of the ...

Tuberculosis detection in chest X-ray using Mayfly-algorithm optimized dual-deep-learning features.

Journal of X-ray science and technology
World-Health-Organization (WHO) has listed Tuberculosis (TB) as one among the top 10 reasons for death and an early diagnosis will help to cure the patient by giving suitable treatment. TB usually affects the lungs and an accurate bio-imaging scheme ...