activity
20232025
most citedAnalysis of the BraTS 2023 Intracranial Meningioma Segmentation Challenge

9 citations · 14 across the 4 of their papers we have counts for

collaborators

4 papers

eess.IV2025

Towards Trustworthy Breast Tumor Segmentation in Ultrasound using Monte Carlo Dropout and Deep Ensembles for Epistemic Uncertainty Estimation

Toufiq Musah, Chinasa Kalaiwo, Maimoona Akram +7

Automated segmentation of BUS images is important for precise lesion delineation and tumor characterization, but is challenged by inherent artifacts and dataset inconsistencies. In…

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.…

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…

eess.IV2023★ 4 cited

The Brain Tumor Segmentation (BraTS) Challenge: Local Synthesis of Healthy Brain Tissue via Inpainting

Florian Kofler, Felix Meissen, Felix Steinbauer +103

A myriad of algorithms for the automatic analysis of brain MR images is available to support clinicians in their decision-making. For brain tumor patients, the image acquisition ti…