390 citations · 538 across the 6 of their papers we have counts for
6 papers
Analysis of the BraTS 2023 Intracranial Meningioma Segmentation Challenge
Dominic LaBella, Ujjwal Baid, Omaditya Khanna +119
We describe the design and results from the BraTS 2023 Intracranial Meningioma Segmentation Challenge. The BraTS Meningioma Challenge differed from prior BraTS Glioma challenges in…
The ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge 2023: Intracranial Meningioma
Dominic LaBella, Maruf Adewole, Michelle Alonso-Basanta +57
Meningiomas are the most common primary intracranial tumor in adults and can be associated with significant morbidity and mortality. Radiologists, neurosurgeons, neuro-oncologists,…
Report of the Medical Image De-Identification (MIDI) Task Group -- Best Practices and Recommendations
David A. Clunie, Adam Flanders, Adam Taylor +16
This report addresses the technical aspects of de-identification of medical images of human subjects and biospecimens, such that re-identification risk of ethical, moral, and legal…
Federated Learning Enables Big Data for Rare Cancer Boundary Detection
Sarthak Pati, Ujjwal Baid, Brandon Edwards +276
Although machine learning (ML) has shown promise in numerous domains, there are concerns about generalizability to out-of-sample data. This is currently addressed by centrally shar…
The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification
Ujjwal Baid, Satyam Ghodasara, Suyash Mohan +100
The BraTS 2021 challenge celebrates its 10th anniversary and is jointly organized by the Radiological Society of North America (RSNA), the American Society of Neuroradiology (ASNR)…
Application of Deep Learning in Neuroradiology: Automated Detection of Basal Ganglia Hemorrhage using 2D-Convolutional Neural Networks
Vishal Desai, Adam E. Flanders, Paras Lakhani
Background: Deep learning techniques have achieved high accuracy in image classification tasks, and there is interest in applicability to neuroimaging critical findings. This study…