1 citations · 2 across the 4 of their papers we have counts for
4 papers
Medical Image De-Identification Resources: Synthetic DICOM Data and Tools for Validation
Michael W. Rutherford, Tracy Nolan, Linmin Pei +10
Medical imaging research increasingly depends on large-scale data sharing to promote reproducibility and train Artificial Intelligence (AI) models. Ensuring patient privacy remains…
Medical Image De-Identification Benchmark Challenge
Linmin Pei, Granger Sutton, Michael Rutherford +67
The de-identification (deID) of protected health information (PHI) and personally identifiable information (PII) is a fundamental requirement for sharing medical images, particular…
AI generated annotations for Breast, Brain, Liver, Lungs and Prostate cancer collections in National Cancer Institute Imaging Data Commons
Gowtham Krishnan Murugesan, Diana McCrumb, Rahul Soni +8
AI in Medical Imaging project aims to enhance the National Cancer Institute's (NCI) Image Data Commons (IDC) by developing nnU-Net models and providing AI-assisted segmentations fo…
AI-Generated Annotations Dataset for Diverse Cancer Radiology Collections in NCI Image Data Commons
Gowtham Krishnan Murugesan, Diana McCrumb, Mariam Aboian +10
The National Cancer Institute (NCI) Image Data Commons (IDC) offers publicly available cancer radiology collections for cloud computing, crucial for developing advanced imaging too…