Federated learning enables big data for rare cancer boundary detection

S Pati, U Baid, B Edwards, M Sheller, SH Wang… - Nature …, 2022 - nature.com
Although machine learning (ML) has shown promise across disciplines, out-of-sample
generalizability is concerning. This is currently addressed by sharing multi-site data, but …

The rsna-asnr-miccai brats 2021 benchmark on brain tumor segmentation and radiogenomic classification

U Baid, S Ghodasara, S Mohan, M Bilello… - arXiv preprint arXiv …, 2021 - arxiv.org
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 …

The University of Pennsylvania glioblastoma (UPenn-GBM) cohort: advanced MRI, clinical, genomics, & radiomics

S Bakas, C Sako, H Akbari, M Bilello, A Sotiras… - Scientific data, 2022 - nature.com
Glioblastoma is the most common aggressive adult brain tumor. Numerous studies have
reported results from either private institutional data or publicly available datasets. However …

Within-modality synthesis and novel radiomic evaluation of brain MRI scans

SM Rezaeijo, N Chegeni, F Baghaei Naeini, D Makris… - Cancers, 2023 - mdpi.com
Simple Summary Brain MRI scans often require different imaging sequences based on
tissue types, posing a common challenge. In our research, we propose a method that utilizes …

The brain tumor segmentation (BraTS) challenge 2023: focus on pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)

AF Kazerooni, N Khalili, X Liu, D Haldar, Z Jiang… - arXiv preprint arXiv …, 2023 - arxiv.org
Pediatric tumors of the central nervous system are the most common cause of cancer-related
death in children. The five-year survival rate for high-grade gliomas in children is less than …

The federated tumor segmentation (fets) challenge

S Pati, U Baid, M Zenk, B Edwards, M Sheller… - arXiv preprint arXiv …, 2021 - arxiv.org
This manuscript describes the first challenge on Federated Learning, namely the Federated
Tumor Segmentation (FeTS) challenge 2021. International challenges have become the …

Radiogenomic classification for MGMT promoter methylation status using multi-omics fused feature space for least invasive diagnosis through mpMRI scans

SA Qureshi, L Hussain, U Ibrar, E Alabdulkreem… - Scientific reports, 2023 - nature.com
Accurate radiogenomic classification of brain tumors is important to improve the standard of
diagnosis, prognosis, and treatment planning for patients with glioblastoma. In this study, we …

The brain tumor segmentation (brats) challenge 2023: glioma segmentation in sub-saharan Africa patient population (brats-africa)

M Adewole, JD Rudie, A Gbadamosi, O Toyobo… - arXiv preprint arXiv …, 2023 - arxiv.org
Gliomas are the most common type of primary brain tumors. Although gliomas are relatively
rare, they are among the deadliest types of cancer, with a survival rate of less than 2 years …

The brain tumor segmentation (brats-mets) challenge 2023: Brain metastasis segmentation on pre-treatment mri

AW Moawad, A Janas, U Baid, D Ramakrishnan… - arXiv preprint arXiv …, 2023 - arxiv.org
Clinical monitoring of metastatic disease to the brain can be a laborious and time-
consuming process, especially in cases involving multiple metastases when the assessment …

Fused deep learning paradigm for the prediction of o6-methylguanine-DNA methyltransferase genotype in glioblastoma patients: a neuro-oncological investigation

S Saxena, B Jena, B Mohapatra, N Gupta… - Computers in Biology …, 2023 - Elsevier
Abstract Background The O6-methylguanine-DNA methyltransferase (MGMT) is a
deoxyribonucleic acid (DNA) repairing enzyme that has been established as an essential …