AIMC Topic: X-Rays

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Using Radiomics as Prior Knowledge for Thorax Disease Classification and Localization in Chest X-rays.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Chest X-ray becomes one of the most common medical diagnoses due to its noninvasiveness. The number of chest X-ray images has skyrocketed, but reading chest X-rays still have been manually performed by radiologists, which creates huge burnouts and de...

COVID-19 mortality prediction in the intensive care unit with deep learning based on longitudinal chest X-rays and clinical data.

European radiology
OBJECTIVES: We aimed to develop deep learning models using longitudinal chest X-rays (CXRs) and clinical data to predict in-hospital mortality of COVID-19 patients in the intensive care unit (ICU).

An Efficient Deep Learning Model to Detect COVID-19 Using Chest X-ray Images.

International journal of environmental research and public health
The tragic pandemic of COVID-19, due to the Severe Acute Respiratory Syndrome coronavirus-2 or SARS-CoV-2, has shaken the entire world, and has significantly disrupted healthcare systems in many countries. Because of the existing challenges and contr...

Fracture Detection in Wrist X-ray Images Using Deep Learning-Based Object Detection Models.

Sensors (Basel, Switzerland)
Hospitals, especially their emergency services, receive a high number of wrist fracture cases. For correct diagnosis and proper treatment of these, images obtained from various medical equipment must be viewed by physicians, along with the patient's ...

Chest X-ray Classification for the Detection of COVID-19 Using Deep Learning Techniques.

Sensors (Basel, Switzerland)
Recent technological developments pave the path for deep learning-based techniques to be used in almost every domain of life. The precision of deep learning techniques make it possible for these to be used in the medical field for the classification ...

Novel-view X-ray projection synthesis through geometry-integrated deep learning.

Medical image analysis
X-ray imaging is a widely used approach to view the internal structure of a subject for clinical diagnosis, image-guided interventions and decision-making. The X-ray projections acquired at different view angles provide complementary information of p...

Performance change with the number of training data: A case study on the binary classification of COVID-19 chest X-ray by using convolutional neural networks.

Computers in biology and medicine
One of the features of artificial intelligence/machine learning-based medical devices resides in their ability to learn from real-world data. However, obtaining a large number of training data in the early phase is difficult, and the device performan...

E-TBNet: Light Deep Neural Network for Automatic Detection of Tuberculosis with X-ray DR Imaging.

Sensors (Basel, Switzerland)
Currently, the tuberculosis (TB) detection model based on chest X-ray images has the problem of excessive reliance on hardware computing resources, high equipment performance requirements, and being harder to deploy in low-cost personal computer and ...

Artificial Intelligence-Based Assistance System for Visual Inspection of X-ray Scatter Grids.

Sensors (Basel, Switzerland)
Convolutional neural network (CNN)-based approaches have recently led to major performance steps in visual recognition tasks. However, only a few industrial applications are described in the literature. In this paper, an object detection application ...