AIMC Topic: Radiography

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[Medical imaging professionals and related specialties : a questioning is essential!].

Revue medicale de Liege
Nowadays, we are facing an overwhelming amount of public announcements concerning the rise of artificial intelligence (AI) in the world of medical imaging (including radiology, nuclear medicine and radiotherapy). While most of the applications are st...

Using a Dual-Input Convolutional Neural Network for Automated Detection of Pediatric Supracondylar Fracture on Conventional Radiography.

Investigative radiology
OBJECTIVES: This study aimed to develop a dual-input convolutional neural network (CNN)-based deep-learning algorithm that utilizes both anteroposterior (AP) and lateral elbow radiographs for the automated detection of pediatric supracondylar fractur...

Development of an Artificial Intelligence Model to Identify a Dental Implant from a Radiograph.

The International journal of oral & maxillofacial implants
PURPOSE: The objective of this study was to develop a deep convolutional neural network (CNN) that would identify the brand and model of a dental implant from a radiograph.

Deep Learning: A Breakthrough in Medical Imaging.

Current medical imaging
Deep learning has attracted great attention in the medical imaging community as a promising solution for automated, fast and accurate medical image analysis, which is mandatory for quality healthcare. Convolutional neural networks and its variants ha...

Quick and accurate selection of hand images among radiographs from various body parts using deep learning.

Journal of X-ray science and technology
BACKGROUND: Although rheumatoid arthritis (RA) causes destruction of articular cartilage, early treatment significantly improves symptoms and delays progression. It is important to detect subtle damage for an early diagnosis. Recent software programs...

Diagnosis of Osteoporosis using modified U-net architecture with attention unit in DEXA and X-ray images.

Journal of X-ray science and technology
BACKGROUND: Osteoporosis, a silent killing disease of fracture risk, is normally determined based on the bone mineral density (BMD) and T-score values measured in bone. However, development of standard algorithms for accurate segmentation and BMD mea...

A Review of Perceptual Expertise in Radiology-How it develops, How we can test it, and Why humans still matter in the era of Artificial Intelligence.

Academic radiology
As the first step in image interpretation is detection, an error in perception can prematurely end the diagnostic process leading to missed diagnoses. Because perceptual errors of this sort-"failure to detect"-are the most common interpretive error (...

The Algorithmic Audit: Working with Vendors to Validate Radiology-AI Algorithms-How We Do It.

Academic radiology
There is a plethora of Artificial Intelligence (AI) tools that are being developed around the world aiming at either speeding up or improving the accuracy of radiologists. It is essential for radiologists to work with the developers of such algorithm...