Results 121 to 130 of about 84,497 (338)

Using Convolutional Neural Networks for the Classification of Suboptimal Chest Radiographs

Journal of Medical Radiation Sciences, EarlyView.
This study evaluated DenseNet121 and YOLOv8 neural networks in detecting suboptimal chest x‐rays for quality control. Through training, validation, and testing, both AI models effectively classified chest X‐ray quality, highlighting the potential to provide radiographers with feedback to enhance image quality.
Emily Huanke Liu, Daniel Carrion, Mohamed Khaldoun Badawy   +2 more
wiley   +1 more source

Digital radiography [PDF]

British Dental Journal, 2008
Penelope Allisy-Roberts, Jerry Williams
openaire   +2 more sources

The quality of radiographs accompanying endodontic referrals to a health authority clinic [PDF]

, 2015
A Bolas, A Butt, A Wenzel, AG Farman, B Vandenberghe, B. S. Chong, BS Chong, CV Devlin, E Borg, E Whaite, G Gerrard, GD Rodgers, J Patel, J Rout, J. Miller, K Hellén-Halme, K Hellén-Halme, K Horner, MK Nair, NA Ting, PF van der Stelt, PF van der Stelt, S. Sidhu, SL Farrier, TM Sommers, WE Berkhout, WE Berkhout   +26 more
core   +1 more source

Radiation Risk in 2D Mammography Screening: A Scoping Review of Modelling Strategies and Emerging AI Applications

Journal of Medical Radiation Sciences, EarlyView.
This scoping review examined models estimating long‐term radiation risks from repeated mammography screening. While modelling indicates the risks are low, approaches vary by protocol and vendor. Emerging AI tools show promise for improving personalised risk estimation, though further development is needed for cross‐platform compatibility.
Nazli A. Moda, Mo'ayyad E. Suleiman, Sahand Hooshmand, Warren M. Reed   +3 more
wiley   +1 more source

Digital mammography, cancer screening: Factors important for image compression [PDF]

The use of digital mammography for breast cancer screening poses several novel problems such as development of digital sensors, computer assisted diagnosis (CAD) methods for image noise suppression, enhancement, and pattern recognition, compression ...
Blaine, G. James, Brown, G. Stephen, Clarke, Laurence P., Doi, Kunio, Kallergi, Maria, Shtern, Faina, Winfield, Daniel L., Yaffe, Martin J.   +7 more
core   +1 more source

Patient Dose Optimisation of Abdominopelvic Protocols During X‐Ray Imaging

Journal of Medical Radiation Sciences, EarlyView.
This study evaluates organ doses in abdominopelvic radiography for both erect and supine positions, addressing dose optimisation concerns in Ghana. Using CalDose X and thermoluminescence dosimeters, organ doses and image quality were analysed, revealing significant dose reductions with optimised exposure parameters (70 kVp, 10 mAs, 110 cm FDD).
Emmanuel Ekem‐Ferguson, Shirazu Issahaku, Mark Pokoo‐Aikins, Mary Boadu   +3 more
wiley   +1 more source

Conventional versus digital radiography in detecting root canal type in maxillary premolars: an in vitro study.

Frontiers in Dentistry, 2013
Successful endodontic therapy depends on adequate mechanical and chemical debridement of the canal which requires knowledge of the canal morphology. Conventional radiography has been used to evaluate the canal type; however, direct digital radiography ...
Mahkameh Moshfeghi, Soodabeh Sadat Sajadi, Sepideh Sajadi, Majid Shahbazian   +3 more
doaj  

The Importance of Patient Positioning in Radiography When Utilising Automatic Exposure Control

Journal of Medical Radiation Sciences, EarlyView.
This study highlights the impact of inaccurate patient positioning on dose and image quality when utilising the automatic exposure control (AEC) for radiographic examinations. While the AEC serves to optimise radiation dose to patients, the results here demonstrate that poor positioning can lead to significant dose implications for patients.
Adam Steward, Cindy Do, Tate Brazil, Mikaela Barresi   +3 more
wiley   +1 more source

The impact of Digital Radiography: is it deskilling our radiographers?

, 2018
Sonyia McFadden
openalex   +1 more source

Experiences of Diagnostic Radiography Students With Workplace‐Based and Online Learning During the COVID‐19 Pandemic: A Study Across Four Higher Education Institutions in South Africa

Journal of Medical Radiation Sciences, EarlyView.
This study explored diagnostic radiography students' learning experiences during COVID‐19 across four South African Higher Education Institutions. Themes included challenges with clinical placements, PPE and online learning, as well as inclusive learning enablers. Findings inform strategies to support students during future crises.
Siyabonga Goodwill Hadebe, Amina Hajat, Lynne Janette Hazell   +2 more
wiley   +1 more source