47 citations · 74 across the 19 of their papers we have counts for
9 papers · 1 filter
SHFormer: Dynamic Spectral Filtering Convolutional Neural Network and High-pass Kernel Generation Transformer for Adaptive MRI Reconstruction
Sriprabha Ramanarayanan, Rahul G. S., Mohammad Al Fahim +3
Attention Mechanism (AM) selectively focuses on essential information for imaging tasks and captures relationships between distant pixel neighborhoods to compute feature representa…
Align-cDAE: Alzheimer's Disease Progression Modeling with Attention-Aligned Conditional Diffusion Auto-Encoder
Ayantika Das, Keerthi Ram, Mohanasankar Sivaprakasam
Generative AI framework-based modeling and prediction of longitudinal human brain images offer an efficient mechanism to track neurodegenerative progression, essential for the asse…
CytoCLIP: Learning Cytoarchitectural Characteristics in Developing Human Brain Using Contrastive Language Image Pre-Training
Pralaypati Ta, Sriram Venkatesaperumal, Keerthi Ram +1
The functions of different regions of the human brain are closely linked to their distinct cytoarchitecture, which is defined by the spatial arrangement and morphology of the cells…
AD-DAE: Alzheimer's Disease Progression Modeling with Unpaired Longitudinal MRI using Diffusion Auto-Encoders
Ayantika Das, Arunima Sarkar, Keerthi Ram +1
Generative modeling frameworks have emerged as an effective approach to capture high-dimensional image distributions from large datasets without requiring domain-specific knowledge…
PosDiffAE: Position-aware Diffusion Auto-encoder For High-Resolution Brain Tissue Classification Incorporating Artifact Restoration
Ayantika Das, Moitreya Chaudhuri, Koushik Bhat +3
Denoising diffusion models produce high-fidelity image samples by capturing the image distribution in a progressive manner while initializing with a simple distribution and compoun…
Detection and skeletonization of single neurons and tracer injections using topological methods
Dingkang Wang, Lucas Magee, Bing-Xing Huo +8
Neuroscientific data analysis has traditionally relied on linear algebra and stochastic process theory. However, the tree-like shapes of neurons cannot be described easily as point…