AIMC Topic: Radiography
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Generalizability and Bias in a Deep Learning Pediatric Bone Age Prediction Model Using Hand Radiographs.
Radiology
Sep 27, 2022
Background Although deep learning (DL) models have demonstrated expert-level ability for pediatric bone age prediction, they have shown poor generalizability and bias in other use cases. Purpose To quantify generalizability and bias in a bone age DL ...
Superlative Feature Selection Based Image Classification Using Deep Learning in Medical Imaging.
Journal of healthcare engineering
Sep 26, 2022
Medical image recognition plays an essential role in the forecasting and early identification of serious diseases in the field of identification. Medical pictures are essential to a patient's health record since they may be used to control, manage, a...
Deep Learning Dramatically Reduces the Work Associated with Image Cataloguing and Analysis: Commentary on an article by Pouria Rouzrokh, MD, MPH, MHPE, et al.: "Applying Deep Learning to Establish a Total Hip Arthroplasty Radiography Registry. A Stepwise Approach".
The Journal of bone and joint surgery. American volume
Sep 21, 2022
Feasibility study of deep-learning-based bone suppression incorporated with single-energy material decomposition technique in chest X-rays.
The British journal of radiology
Sep 19, 2022
OBJECTIVE: To improve the detection of lung abnormalities in chest X-rays by accurately suppressing overlapping bone structures in the lung area. According to literature on missed lung cancer in chest X-rays, such structures are a significant cause o...
Singapore radiographers' perceptions and expectations of artificial intelligence - A qualitative study.
Journal of medical imaging and radiation sciences
Sep 15, 2022
INTRODUCTION: With the emergence of artificial intelligence (AI) in medical imaging, radiographers are likely to be at the forefront of this technological advancement. Studies have therefore been conducted recently to understand radiographers' opinio...
Comparison of AudaxCeph®'s fully automated cephalometric tracing technology to a semi-automated approach by human examiners.
International orthodontics
Sep 14, 2022
OBJECTIVE: To compare the reliability of cephalometric landmark identification by an automated tracing software based on convolutional neural networks to human tracers.
Performance comparison of three deep learning models for impacted mesiodens detection on periapical radiographs.
Scientific reports
Sep 13, 2022
This study aimed to develop deep learning models that automatically detect impacted mesiodens on periapical radiographs of primary and mixed dentition using the YOLOv3, RetinaNet, and EfficientDet-D3 algorithms and to compare their performance. Peria...
The effect of a deep-learning tool on dentists' performances in detecting apical radiolucencies on periapical radiographs.
Dento maxillo facial radiology
Sep 12, 2022
OBJECTIVES: To determine the efficacy of a deep-learning (DL) tool in assisting dentists in detecting apical radiolucencies on periapical radiographs.
Attention UW-Net: A fully connected model for automatic segmentation and annotation of chest X-ray.
Computers in biology and medicine
Sep 10, 2022
BACKGROUND AND OBJECTIVE: Automatic segmentation and annotation of medical image plays a critical role in scientific research and the medical care community. Automatic segmentation and annotation not only increase the efficiency of clinical workflow,...
Deep Learning Assistance Closes the Accuracy Gap in Fracture Detection Across Clinician Types.
Clinical orthopaedics and related research
Sep 9, 2022
BACKGROUND: Missed fractures are the most common diagnostic errors in musculoskeletal imaging and can result in treatment delays and preventable morbidity. Deep learning, a subfield of artificial intelligence, can be used to accurately detect fractur...
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