30 citations · 34 across the 5 of their papers we have counts for
5 papers
Training the next generation of physicians for artificial intelligence-assisted clinical neuroradiology: ASNR MICCAI Brain Tumor Segmentation (BraTS) 2025 Lighthouse Challenge education platform
Raisa Amiruddin, Nikolay Y. Yordanov, Nazanin Maleki +45
High-quality reference standard image data creation by neuroradiology experts for automated clinical tools can be a powerful tool for neuroradiology & artificial intelligence educa…
Analysis of the MICCAI Brain Tumor Segmentation -- Metastases (BraTS-METS) 2025 Lighthouse Challenge: Brain Metastasis Segmentation on Pre- and Post-treatment MRI
Nazanin Maleki, Raisa Amiruddin, Ahmed W. Moawad +240
Despite continuous advancements in cancer treatment, brain metastatic disease remains a significant complication of primary cancer and is associated with an unfavorable prognosis.…
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…
A Large Open Access Dataset of Brain Metastasis 3D Segmentations with Clinical and Imaging Feature Information
Divya Ramakrishnan, Leon Jekel, Saahil Chadha +19
Resection and whole brain radiotherapy (WBRT) are the standards of care for the treatment of patients with brain metastases (BM) but are often associated with cognitive side effect…
The Brain Tumor Segmentation (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI
Ahmed W. Moawad, Anastasia Janas, Ujjwal Baid +229
The translation of AI-generated brain metastases (BM) segmentation into clinical practice relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS-METS…