activity
20222025
most citedFederated Learning Enables Big Data for Rare Cancer Boundary Detection

390 citations · 425 across the 5 of their papers we have counts for

collaborators

5 papers

q-bio.OT2025★ 1 cited

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.…

cs.CV2024★ 18 cited

The 2024 Brain Tumor Segmentation (BraTS) Challenge: Glioma Segmentation on Post-treatment MRI

Maria Correia de Verdier, Rachit Saluja, Louis Gagnon +82

Gliomas are the most common malignant primary brain tumors in adults and one of the deadliest types of cancer. There are many challenges in treatment and monitoring due to the gene…

cs.CV2024★ 7 cited

Analysis of the 2024 BraTS Meningioma Radiotherapy Planning Automated Segmentation Challenge

Dominic LaBella, Valeriia Abramova, Mehdi Astaraki +102

The 2024 Brain Tumor Segmentation Meningioma Radiotherapy (BraTS-MEN-RT) challenge aimed to advance automated segmentation algorithms using the largest known multi-institutional da…

eess.IV2024★ 9 cited

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…

cs.LG2022★ 390 cited

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…