AIMC Topic: Radiography
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Deep learning-based classification of primary bone tumors on radiographs: A preliminary study.
EBioMedicine
Nov 22, 2020
BACKGROUND: To develop a deep learning model to classify primary bone tumors from preoperative radiographs and compare performance with radiologists.
Smart chest X-ray worklist prioritization using artificial intelligence: a clinical workflow simulation.
European radiology
Nov 21, 2020
OBJECTIVE: The aim is to evaluate whether smart worklist prioritization by artificial intelligence (AI) can optimize the radiology workflow and reduce report turnaround times (RTATs) for critical findings in chest radiographs (CXRs). Furthermore, we ...
Compressed sensing and deep learning reconstruction for women's pelvic MRI denoising: Utility for improving image quality and examination time in routine clinical practice.
European journal of radiology
Nov 21, 2020
PURPOSE: To demonstrate the utility of compressed sensing with parallel imaging (Compressed SPEEDER) and AiCE compared with that of conventional parallel imaging (SPEEDER) for shortening examination time and improving image quality of women's pelvic ...
Machine learning in cardiovascular radiology: ESCR position statement on design requirements, quality assessment, current applications, opportunities, and challenges.
European radiology
Nov 19, 2020
Machine learning offers great opportunities to streamline and improve clinical care from the perspective of cardiac imagers, patients, and the industry and is a very active scientific research field. In light of these advances, the European Society o...
Cascaded convolutional networks for automatic cephalometric landmark detection.
Medical image analysis
Nov 18, 2020
Cephalometric analysis is a fundamental examination which is widely used in orthodontic diagnosis and treatment planning. Its key step is to detect the anatomical landmarks in lateral cephalograms, which is time-consuming in traditional manual way. T...
Artificial intelligence for the detection of vertebral fractures on plain spinal radiography.
Scientific reports
Nov 18, 2020
Vertebral fractures (VFs) cause serious problems, such as substantial functional loss and a high mortality rate, and a delayed diagnosis may further worsen the prognosis. Plain thoracolumbar radiography (PTLR) is an essential method for the evaluatio...
Artificial Intelligence to Identify Arthroplasty Implants From Radiographs of the Hip.
The Journal of arthroplasty
Nov 16, 2020
BACKGROUND: The surgical management of complications surrounding patients who have undergone hip arthroplasty necessitates accurate identification of the femoral implant manufacturer and model. Failure to do so risks delays in care, increased morbidi...
Artificial intelligence in oral and maxillofacial radiology: what is currently possible?
Dento maxillo facial radiology
Nov 16, 2020
Artificial intelligence, which has been actively applied in a broad range of industries in recent years, is an active area of interest for many researchers. Dentistry is no exception to this trend, and the applications of artificial intelligence are ...
Potential use of deep learning techniques for postmortem imaging-moving beyond postmortem radiology.
Forensic science, medicine, and pathology
Nov 11, 2020
Deep Learning for Osteoporosis Classification Using Hip Radiographs and Patient Clinical Covariates.
Biomolecules
Nov 10, 2020
This study considers the use of deep learning to diagnose osteoporosis from hip radiographs, and whether adding clinical data improves diagnostic performance over the image mode alone. For objective labeling, we collected a dataset containing 1131 im...
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