13 citations · 27 across the 7 of their papers we have counts for
7 papers
T-SYNTH: A Knowledge-Based Dataset of Synthetic Breast Images
Christopher Wiedeman, Anastasiia Sarmakeeva, Elena Sizikova +4
One of the key impediments for developing and assessing robust medical imaging algorithms is limited access to large-scale datasets with suitable annotations. Synthetic data genera…
S-SYNTH: Knowledge-Based, Synthetic Generation of Skin Images
Andrea Kim, Niloufar Saharkhiz, Elena Sizikova +4
Development of artificial intelligence (AI) techniques in medical imaging requires access to large-scale and diverse datasets for training and evaluation. In dermatology, obtaining…
Synthetic Data in Radiological Imaging: Current State and Future Outlook
Elena Sizikova, Andreu Badal, Jana G. Delfino +6
A key challenge for the development and deployment of artificial intelligence (AI) solutions in radiology is solving the associated data limitations. Obtaining sufficient and repre…
Scorecards for Synthetic Medical Data Evaluation and Reporting
Ghada Zamzmi, Adarsh Subbaswamy, Elena Sizikova +3
Although interest in synthetic medical data (SMD) for training and testing AI methods is growing, the absence of a standardized framework to evaluate its quality and applicability…
Knowledge-based in silico models and dataset for the comparative evaluation of mammography AI for a range of breast characteristics, lesion conspicuities and doses
Elena Sizikova, Niloufar Saharkhiz, Diksha Sharma +4
To generate evidence regarding the safety and efficacy of artificial intelligence (AI) enabled medical devices, AI models need to be evaluated on a diverse population of patient ca…
The stochastic digital human is now enrolling for in silico imaging trials -- Methods and tools for generating digital cohorts
A Badano, M Lago, E Sizikova +4
Randomized clinical trials, while often viewed as the highest evidentiary bar by which to judge the quality of a medical intervention, are far from perfect. In silico imaging trial…
CASS: Cross Architectural Self-Supervision for Medical Image Analysis
Pranav Singh, Elena Sizikova, Jacopo Cirrone
Recent advances in deep learning and computer vision have reduced many barriers to automated medical image analysis, allowing algorithms to process label-free images and improve pe…