The rsna-asnr-miccai brats 2021 benchmark on brain tumor segmentation and radiogenomic classification
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 …
Radiological Society of North America (RSNA), the American Society of Neuroradiology …
[HTML][HTML] Federated learning enables big data for rare cancer boundary detection
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 …
generalizability is concerning. This is currently addressed by sharing multi-site data, but …
[HTML][HTML] The University of Pennsylvania glioblastoma (UPenn-GBM) cohort: advanced MRI, clinical, genomics, & radiomics
Glioblastoma is the most common aggressive adult brain tumor. Numerous studies have
reported results from either private institutional data or publicly available datasets. However …
reported results from either private institutional data or publicly available datasets. However …
The federated tumor segmentation (fets) challenge
This manuscript describes the first challenge on Federated Learning, namely the Federated
Tumor Segmentation (FeTS) challenge 2021. International challenges have become the …
Tumor Segmentation (FeTS) challenge 2021. International challenges have become the …
[HTML][HTML] Radiogenomic classification for MGMT promoter methylation status using multi-omics fused feature space for least invasive diagnosis through mpMRI scans
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 …
diagnosis, prognosis, and treatment planning for patients with glioblastoma. In this study, we …
[HTML][HTML] Within-modality synthesis and novel radiomic evaluation of brain MRI scans
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 …
tissue types, posing a common challenge. In our research, we propose a method that utilizes …
[HTML][HTML] The brain tumor segmentation (BRATS) challenge 2023: Focus on pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)
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 …
death in children. The five-year survival rate for high-grade gliomas in children is less than …
[HTML][HTML] Clinical measures, radiomics, and genomics offer synergistic value in AI-based prediction of overall survival in patients with glioblastoma
Multi-omic data, ie, clinical measures, radiomic, and genetic data, capture multi-faceted
tumor characteristics, contributing to a comprehensive patient risk assessment. Here, we …
tumor characteristics, contributing to a comprehensive patient risk assessment. Here, we …
The brain tumor sequence registration challenge: establishing correspondence between pre-operative and follow-up MRI scans of diffuse glioma patients
Registration of longitudinal brain Magnetic Resonance Imaging (MRI) scans containing
pathologies is challenging due to tissue appearance changes, and still an unsolved …
pathologies is challenging due to tissue appearance changes, and still an unsolved …
[HTML][HTML] Visualizing glioma infiltration by the combination of multimodality imaging and artificial intelligence, a systematic review of the literature
SH d'Este, MB Nielsen, AE Hansen - Diagnostics, 2021 - mdpi.com
The aim of this study was to systematically review the literature concerning the integration of
multimodality imaging with artificial intelligence methods for visualization of tumor cell …
multimodality imaging with artificial intelligence methods for visualization of tumor cell …