AIMC Topic: Radiography

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Deep learning for chest X-ray analysis: A survey.

Medical image analysis
Recent advances in deep learning have led to a promising performance in many medical image analysis tasks. As the most commonly performed radiological exam, chest radiographs are a particularly important modality for which a variety of applications h...

Development of retake support system for lateral knee radiographs by using deep convolutional neural network.

Radiography (London, England : 1995)
INTRODUCTION: Lateral radiography of the knee joint is frequently performed; however, the retake rate is high owing to positioning errors. Therefore, in this study, to reduce the required number and time of image retakes, we developed a system that c...

Deep Learning-Based End-to-End Diagnosis System for Avascular Necrosis of Femoral Head.

IEEE journal of biomedical and health informatics
As the first diagnostic imaging modality of avascular necrosis of the femoral head (AVNFH), accurately staging AVNFH from a plain radiograph is critical yet challenging for orthopedists. Thus, we propose a deep learning-based AVNFH diagnosis system (...

Deep learning for cephalometric landmark detection: systematic review and meta-analysis.

Clinical oral investigations
OBJECTIVES: Deep learning (DL) has been increasingly employed for automated landmark detection, e.g., for cephalometric purposes. We performed a systematic review and meta-analysis to assess the accuracy and underlying evidence for DL for cephalometr...

Toward understanding COVID-19 pneumonia: a deep-learning-based approach for severity analysis and monitoring the disease.

Scientific reports
We report a new approach using artificial intelligence (AI) to study and classify the severity of COVID-19 using 1208 chest X-rays (CXRs) of 396 COVID-19 patients obtained through the course of the disease at Emory Healthcare affiliated hospitals (At...

Performance of deep learning technology for evaluation of positioning quality in periapical radiography of the maxillary canine.

Oral radiology
OBJECTIVES: The aim of the present study was to create and test an automatic system for assessing the technical quality of positioning in periapical radiography of the maxillary canines using deep learning classification and segmentation techniques.

Enhancing the X-Ray Differential Phase Contrast Image Quality With Deep Learning Technique.

IEEE transactions on bio-medical engineering
OBJECTIVE: The purpose of this work is to investigate the feasibility of using deep convolutional neural network (CNN) to improve the image quality of a grating-based X-ray differential phase contrast imaging (XPCI) system.

Evaluating subscapularis tendon tears on axillary lateral radiographs using deep learning.

European radiology
OBJECTIVE: To develop a deep learning algorithm capable of evaluating subscapularis tendon (SSC) tears based on axillary lateral shoulder radiography.

Radiomics and deep learning methods in expanding the use of screening breast MRI.

European radiology
• The use of screening breast MRI is expanding beyond high-risk women to include intermediate- and average-risk women.• The study by Pötsch et al uses a radiomics-based method to decrease the number of benign biopsies while maintaining high sensitivi...