58 citations · 59 across the 3 of their papers we have counts for
3 papers
eess.IV2021★ 58 cited
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.…
cs.LG2021★ 1 cited
Improving the Algorithm of Deep Learning with Differential Privacy
Mehdi Amian
In this paper, an adjustment to the original differentially private stochastic gradient descent (DPSGD) algorithm for deep learning models is proposed. As a matter of motivation, t…
eess.IV2019
Multi-Resolution 3D CNN for MRI Brain Tumor Segmentation and Survival Prediction
Mehdi Amian, Mohammadreza Soltaninejad
In this study, an automated three dimensional (3D) deep segmentation approach for detecting gliomas in 3D pre-operative MRI scans is proposed. Then, a classi-fication algorithm bas…