AIMC Topic: Radiography

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Deep Learning in the Detection and Diagnosis of COVID-19 Using Radiology Modalities: A Systematic Review.

Journal of healthcare engineering
INTRODUCTION: The early detection and diagnosis of COVID-19 and the accurate separation of non-COVID-19 cases at the lowest cost and in the early stages of the disease are among the main challenges in the current COVID-19 pandemic. Concerning the nov...

Review of Artificial Intelligence Training Tools and Courses for Radiologists.

Academic radiology
Artificial intelligence (AI) systems play an increasingly important role in all parts of the imaging chain, from image creation to image interpretation to report generation. In order to responsibly manage radiology AI systems and make informed purcha...

Prediction of the duration needed to achieve culture negativity in patients with active pulmonary tuberculosis using convolutional neural networks and chest radiography.

Respiratory investigation
BACKGROUND: We aimed to predict the duration needed to achieve culture negativity in patients with active pulmonary tuberculosis using convolutional neural networks (CNNs) and chest radiography.

To buy or not to buy-evaluating commercial AI solutions in radiology (the ECLAIR guidelines).

European radiology
Artificial intelligence (AI) has made impressive progress over the past few years, including many applications in medical imaging. Numerous commercial solutions based on AI techniques are now available for sale, forcing radiology practices to learn h...

Deep Anatomical Context Feature Learning for Cephalometric Landmark Detection.

IEEE journal of biomedical and health informatics
In the past decade, anatomical context features have been widely used for cephalometric landmark detection and significant progress is still being made. However, most existing methods rely on handcrafted graphical models rather than incorporating ana...

Dental disease detection on periapical radiographs based on deep convolutional neural networks.

International journal of computer assisted radiology and surgery
OBJECTIVES: It is with a great prospect to develop an auxiliary diagnosis system for dental periapical radiographs based on deep convolutional neural networks (CNNs), and the indications and performances should be investigated. The aim of this study ...

Deep neural networks with promising diagnostic accuracy for the classification of atypical femoral fractures.

Acta orthopaedica
Background and purpose - A correct diagnosis is essential for the appropriate treatment of patients with atypical femoral fractures (AFFs). The diagnostic accuracy of radiographs with standard radiology reports is very poor. We derived a diagnostic a...