216 citations · 443 across the 20 of their papers we have counts for
22 papers
3D Brainformer: 3D Fusion Transformer for Brain Tumor Segmentation
Rui Nian, Guoyao Zhang, Yao Sui +6
Magnetic resonance imaging (MRI) is critically important for brain mapping in both scientific research and clinical studies. Precise segmentation of brain tumors facilitates clinic…
qDWI-Morph: Motion-compensated quantitative Diffusion-Weighted MRI analysis for fetal lung maturity assessment
Yael Zaffrani-Reznikov, Onur Afacan, Sila Kurugol +2
Quantitative analysis of fetal lung Diffusion-Weighted MRI (DWI) data shows potential in providing quantitative imaging biomarkers that indirectly reflect fetal lung maturation. Ho…
Automated modeling of brain bioelectric activity within the 3D Slicer environment
Saima Safdar, Benjamin Zwick, George Bourantas +5
Electrocorticography (ECoG) or intracranial electroencephalography (iEEG) monitors electric potential directly on the surface of the brain and can be used to inform treatment plann…
SUPER-IVIM-DC: Intra-voxel incoherent motion based Fetal lung maturity assessment from limited DWI data using supervised learning coupled with data-consistency
Noam Korngut, Elad Rotman, Onur Afacan +5
Intra-voxel incoherent motion (IVIM) analysis of fetal lungs Diffusion-Weighted MRI (DWI) data shows potential in providing quantitative imaging bio-markers that reflect, indirectl…
CORPS: Cost-free Rigorous Pseudo-labeling based on Similarity-ranking for Brain MRI Segmentation
Can Taylan Sari, Sila Kurugol, Onur Afacan +1
Segmentation of brain magnetic resonance images (MRI) is crucial for the analysis of the human brain and diagnosis of various brain disorders. The drawbacks of time-consuming and e…
Diffusion Tensor Estimation with Uncertainty Calibration
Davood Karimi, Simon K. Warfield, Ali Gholipour
It is highly desirable to know how uncertain a model's predictions are, especially for models that are complex and hard to understand as in deep learning. Although there has been a…