AIMC Topic: Radiography

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A systematic review: Chest radiography images (X-ray images) analysis and COVID-19 categorization diagnosis using artificial intelligence techniques.

Network (Bristol, England)
COVID-19 pandemic created a turmoil across nations due to Severe Acute Respiratory Syndrome Corona virus-1(SARS - Co-V-2). The severity of COVID-19 symptoms is starting from cold, breathing problems, issues in respiratory system which may also lead t...

Scientific Advances and Technical Innovations in Musculoskeletal Radiology.

Investigative radiology
Decades of technical innovations have propelled musculoskeletal radiology through an astonishing evolution. New artificial intelligence and deep learning methods capitalize on many past innovations in magnetic resonance imaging (MRI) to reach unprece...

Application of artificial intelligence to imaging interpretations in the musculoskeletal area: Where are we? Where are we going?

Joint bone spine
The interest of researchers, clinicians and radiologists, in artificial intelligence (AI) continues to grow. Deep learning is a subset of machine learning, in which the computer algorithm itself can determine the optimal imaging features to answer a ...

Automated Detection of Surgical Implants on Plain Knee Radiographs Using a Deep Learning Algorithm.

Medicina (Kaunas, Lithuania)
: The number of patients who undergo multiple operations on a knee is increasing. The objective of this study was to develop a deep learning algorithm that could detect 17 different surgical implants on plain knee radiographs. : An internal dataset c...

Artificial intelligence system for automated landmark localization and analysis of cephalometry.

Dento maxillo facial radiology
OBJECTIVES: Cephalometric analysis is essential for diagnosis, treatment planning and outcome assessment of orthodontics and orthognathic surgery. Utilizing artificial intelligence (AI) to achieve automated landmark localization has proved feasible a...

Applying Deep Learning for Breast Cancer Detection in Radiology.

Current oncology (Toronto, Ont.)
Recent advances in deep learning have enhanced medical imaging research. Breast cancer is the most prevalent cancer among women, and many applications have been developed to improve its early detection. The purpose of this review is to examine how va...

The impact of artificial intelligence on radiography as a profession: A narrative review.

Journal of medical imaging and radiation sciences
BACKGROUND AND PURPOSE: Artificial intelligence (AI) algorithms, particularly deep learning, have made significant strides in image recognition and classification, providing remarkable diagnostic accuracy to various diseases. This domain of AI has be...

Bone tumor necrosis rate detection in few-shot X-rays based on deep learning.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Although biopsy-based necrosis rate is a golden standard for reflecting the sensitivity of bone tumor and guiding postoperative chemotherapy, it requires biopsy which is invasive and time-consuming. In this paper, we develop a new necrosis rate detec...