100 citations · 253 across the 19 of their papers we have counts for
5 papers · 1 filter
-NeAS: Scalable Multi-Material CT Reconstruction Using Neural SDFs
Daksh K. Shah, Emmanouil Nikolakakis, Razvan Marinescu
Computed Tomography (CT) carries significant ionizing radiation risks, driving the need for sparse-view reconstruction. Implicit scene representations (ISRs) address this by recove…
RibPull: Implicit Occupancy Fields and Medial Axis Extraction for CT Ribcage Scans
Emmanouil Nikolakakis, Amine Ouasfi, Julie Digne +1
We present RibPull, a methodology that utilizes implicit occupancy fields to bridge computational geometry and medical imaging. Implicit 3D representations use continuous functions…
BMapEst: Estimation of Brain Tissue Probability Maps using a Differentiable MRI Simulator
Utkarsh Gupta, Emmanouil Nikolakakis, Moritz Zaiss +1
Reconstructing digital brain phantoms in the form of voxel-based, multi-channeled tissue probability maps for individual subjects is essential for capturing brain anatomical variab…
Bayesian Image Reconstruction using Deep Generative Models
Razvan V Marinescu, Daniel Moyer, Polina Golland
Machine learning models are commonly trained end-to-end and in a supervised setting, using paired (input, output) data. Examples include recent super-resolution methods that train…
DIVE: A spatiotemporal progression model of brain pathology in neurodegenerative disorders
Razvan V. Marinescu, Arman Eshaghi, Marco Lorenzi +5
Here we present DIVE: Data-driven Inference of Vertexwise Evolution. DIVE is an image-based disease progression model with single-vertex resolution, designed to reconstruct long-te…