375 citations · 935 across the 9 of their papers we have counts for
10 papers
QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking Results
Raghav Mehta, Angelos Filos, Ujjwal Baid +89
Deep learning (DL) models have provided state-of-the-art performance in various medical imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) challenges.…
Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge
Hugo J. Kuijf, J. Matthijs Biesbroek, Jeroen de Bresser +41
Quantification of cerebral white matter hyperintensities (WMH) of presumed vascular origin is of key importance in many neurological research studies. Currently, measurements are o…
Multiple Sclerosis Lesion Synthesis in MRI using an encoder-decoder U-NET
Mostafa Salem, Sergi Valverde, Mariano Cabezas +5
In this paper, we propose generating synthetic multiple sclerosis (MS) lesions on MRI images with the final aim to improve the performance of supervised machine learning algorithms…
Survival prediction using ensemble tumor segmentation and transfer learning
Mariano Cabezas, Sergi Valverde, Sandra González-Villà +6
Segmenting tumors and their subregions is a challenging task as demonstrated by the annual BraTS challenge. Moreover, predicting the survival of the patient using mainly imaging fe…
Acute and sub-acute stroke lesion segmentation from multimodal MRI
Albert Clèrigues, Sergi Valverde, Jose Bernal +3
Acute stroke lesion segmentation tasks are of great clinical interest as they can help doctors make better informed treatment decisions. Magnetic resonance imaging (MRI) is time de…
One-shot domain adaptation in multiple sclerosis lesion segmentation using convolutional neural networks
Sergi Valverde, Mostafa Salem, Mariano Cabezas +7
In recent years, several convolutional neural network (CNN) methods have been proposed for the automated white matter lesion segmentation of multiple sclerosis (MS) patient images,…