A training and assessment package for digital mammographySumsion, H. J.Parkin, G. J. S.Cowen, A. R.EXCERPTA MEDICA INTERNATIONAL CONGRESS SERIES
Introduction Correct alignment of the image receptor (IR) in mammography for the mediolateral oblique (MLO) view of the breast is fundamental to enable the maximum inclusion of breast tissue. This study aims to assess Australian radiographers' knowledge and digital era practice in selecting the IR ...
AIM: The aim of the study was to compare mammography assessments using three types of AI services in multiple versions with radiologists’ conclusions. MATERIALS AND METHODS: Binary mammography scoring scales were compared with several types and versions of AI services regarding diagnostic accuracy, Mat...
Interpretability in machine learning models is important in high-stakes decisions such as whether to order a biopsy based on a mammographic exam. Mammography poses important challenges that are not present in other computer vision tasks: datasets are sma
They used “Digital Database for Screening Mammography” (DDSM), which consists of normal and cancerous images. The accuracy decreased up to 30% while the Structural Similarity Index SSIM index fell below 0.2. Pal et al. [16] applied FGSM attack on X-rays and CT-Scans for COVID-19 ...
Available online: https://www.kaggle.com/datasets/kmader/mias-mammography (accessed on 12 June 2023). Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the edito...
Screening performance and characteristics of breast cancer detected in the Mammography Screening with Artificial Intelligence trial (MASAI): a randomised, controlled, parallel-group, non-inferiority, single-blinded, screening accuracy study Veronica Hernström, ... Kristina LångMarch 2025View PDF Resear...
Therefore, the aim of the presented pilot study was to learn more about the personal motives and attitudes of SPs as well as their initial training experiences when participating in the DRE for the first time. Methods Study design We conducted a descriptive study to investigate the personal back...
Cover the full spectrum of multimodal diagnostics from mammography to MRI and ultrasound. Collaborative outcomes Connect healthcare IT systems to enable collaboration and communication between care teams, Enterprise and patients to advance collaborative outcomes. ...
Deep learning (DL) has the potential to transform medical diagnostics. However, the diagnostic accuracy of DL is uncertain. Our aim was to evaluate the diagnostic accuracy of DL algorithms to identify pathology in medical imaging. Searches were conducted