AIMC Topic: Radiography
Clear Filters Showing 761 to 770 of 1088 articles
Automated feature detection in dental periapical radiographs by using deep learning.
Oral surgery, oral medicine, oral pathology and oral radiology
Aug 27, 2020
OBJECTIVE: The aim of this study was to investigate automated feature detection, segmentation, and quantification of common findings in periapical radiographs (PRs) by using deep learning (DL)-based computer vision techniques.
Patient Safety: Considerations for Artificial Intelligence Implementation in Radiology.
Journal of the American College of Radiology : JACR
Aug 27, 2020
Making Your AI Smarter: Continuous Learning Artificial Intelligence for Radiology.
Radiology
Aug 25, 2020
Comment on "Robot-Assisted versus Conventional Total and Unicompartmental Knee Arthroplasty: A Meta-analysis of Radiological and Functional Outcomes".
The journal of knee surgery
Aug 24, 2020
Cancer Informatics in 2019: Deep Learning Takes Center Stage.
Yearbook of medical informatics
Aug 21, 2020
OBJECTIVE: To summarize significant research contributions on cancer informatics published in 2019.
PadChest: A large chest x-ray image dataset with multi-label annotated reports.
Medical image analysis
Aug 20, 2020
We present a labeled large-scale, high resolution chest x-ray dataset for the automated exploration of medical images along with their associated reports. This dataset includes more than 160,000 images obtained from 67,000 patients that were interpre...
Automated classification of hip fractures using deep convolutional neural networks with orthopedic surgeon-level accuracy: ensemble decision-making with antero-posterior and lateral radiographs.
Acta orthopaedica
Aug 12, 2020
Background and purpose - Deep-learning approaches based on convolutional neural networks (CNNs) are gaining interest in the medical imaging field. We evaluated the diagnostic performance of a CNN to discriminate femoral neck fractures, trochanteric f...
Artificial Intelligence Solutions for Analysis of X-ray Images.
Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
Aug 6, 2020
Artificial intelligence (AI) presents a key opportunity for radiologists to improve quality of care and enhance the value of radiology in patient care and population health. The potential opportunity of AI to aid in triage and interpretation of conve...
Deep convolutional neural network-based anomaly detection for organ classification in gastric X-ray examination.
Computers in biology and medicine
Jul 8, 2020
AIM: The aim of this study was to determine whether our deep convolutional neural network-based anomaly detection model can distinguish differences in esophagus images and stomach images obtained from gastric X-ray examinations.
Differentiation Between Anteroposterior and Posteroanterior Chest X-Ray View Position With Convolutional Neural Networks.
RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin
Jul 2, 2020
PURPOSE: Detection and validation of the chest X-ray view position with use of convolutional neural networks to improve meta-information for data cleaning within a hospital data infrastructure.
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