2 citations · 4 across the 4 of their papers we have counts for
5 papers
STRIDE: Spatial-Temporal Representation for Interval-conditioned Disease Evolution in Longitudinal Glioblastoma MRI
Wenhao Guo, Changchang Yin, Pierre Giglio +3
Glioblastoma (GBM), an aggressive primary brain tumor, is routinely monitored with longitudinal MRI after treatment. Distinguishing stable disease (SD), pseudoprogression (PsP), an…
Variance-Penalized MC-Dropout as a Learned Smoothing Prior for Brain Tumour Segmentation
Satyaki Roy Chowdhury, Golrokh Mirzaei
Brain tumor segmentation is essential for diagnosis and treatment planning, yet many CNN and U-Net based approaches produce noisy boundaries in regions of tumor infiltration. We in…
Timepoint-Specific Benchmarking of Deep Learning Models for Glioblastoma Follow-Up MRI
Wenhao Guo, Golrokh Mirzaei
Differentiating true tumor progression (TP) from treatment-related pseudoprogression (PsP) in glioblastoma remains challenging, especially at early follow-up. We present the first…
Radiogenomic Bipartite Graph Representation Learning for Alzheimer's Disease Detection
Aditya Raj, Golrokh Mirzaei
Imaging and genomic data offer distinct and rich features, and their integration can unveil new insights into the complex landscape of diseases. In this study, we present a novel a…
Hybridization of Attention UNet with Repeated Atrous Spatial Pyramid Pooling for Improved Brain Tumour Segmentation
Satyaki Roy Chowdhury, Golrokh Mirzaei
Brain tumors are highly heterogeneous in terms of their spatial and scaling characteristics, making tumor segmentation in medical images a difficult task that might result in wrong…