4 citations · 5 across the 4 of their papers we have counts for
5 papers
CarveMix-RC: Addressing Rare-Class Imbalance Through Lesion-Aware Synthetic Augmentation for Brain Metastasis Segmentation
Md Shibly Sadique, Md Fayaz Bin Hossen, Michael L. Evans +4
Accurate segmentation of post-treatment brain metastases is essential for treatment planning, longitudinal disease monitoring, and quantitative assessment of therapeutic response.…
Machine learning-enhanced non-amnestic Alzheimer's disease diagnosis from MRI and clinical features
Megan A. Witherow, Michael L. Evans, Ahmed Temtam +2
Alzheimer's disease (AD), defined as an abnormal buildup of amyloid plaques and tau tangles in the brain can be diagnosed with high accuracy based on protein biomarkers via PET or…
Functional Brain Network Identification in Opioid Use Disorder Using Machine Learning Analysis of Resting-State fMRI BOLD Signals
Ahmed Temtam, Megan A. Witherow, Liangsuo Ma +3
Understanding the neurobiology of opioid use disorder (OUD) using resting-state functional magnetic resonance imaging (rs-fMRI) may help inform treatment strategies to improve pati…
Brain Tumor Recurrence vs. Radiation Necrosis Classification and Patient Survivability Prediction
M. S. Sadique, W. Farzana, A. Temtam +3
GBM (Glioblastoma multiforme) is the most aggressive type of brain tumor in adults that has a short survival rate even after aggressive treatment with surgery and radiation therapy…
The Brain Tumor Segmentation (BraTS) Challenge: Local Synthesis of Healthy Brain Tissue via Inpainting
Florian Kofler, Felix Meissen, Felix Steinbauer +103
A myriad of algorithms for the automatic analysis of brain MR images is available to support clinicians in their decision-making. For brain tumor patients, the image acquisition ti…