762 citations · 1.2k across the 4 of their papers we have counts for
5 papers · 1 filter
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…
Automated brain extraction of multi-sequence MRI using artificial neural networks
Fabian Isensee, Marianne Schell, Irada Tursunova +10
Brain extraction is a critical preprocessing step in the analysis of MRI neuroimaging studies and influences the accuracy of downstream analyses. The majority of brain extraction a…
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
Spyridon Bakas, Mauricio Reyes, Andras Jakab +421
Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritum…
No New-Net
Fabian Isensee, Philipp Kickingereder, Wolfgang Wick +2
In this paper we demonstrate the effectiveness of a well trained U-Net in the context of the BraTS 2018 challenge. This endeavour is particularly interesting given that researchers…
Brain Tumor Segmentation and Radiomics Survival Prediction: Contribution to the BRATS 2017 Challenge
Fabian Isensee, Philipp Kickingereder, Wolfgang Wick +2
Quantitative analysis of brain tumors is critical for clinical decision making. While manual segmentation is tedious, time consuming and subjective, this task is at the same time v…