5 papers · 1 filter
MRIComp4Flow: Compression of 3D Brain MRI for Training Multi-Modal Generative Models
Lisa K. Fischer, Mykhailo Riabets, Daniel Rueckert +3
Large-scale multi-modal MRI datasets impose substantial storage and I/O costs, limiting the training of 3D generative models on commodity infrastructure. While lossy compression is…
TumorFlow: Physics-Guided Longitudinal MRI Synthesis of Glioblastoma Growth
Valentin Biller, Niklas Bubeck, Lucas Zimmer +6
Glioblastoma exhibits diverse, infiltrative, and patient-specific growth patterns that are only partially visible on routine MRI, making it difficult to reliably assess true tumor…
Fast & Efficient Normalizing Flows and Applications of Image Generative Models
Sandeep Nagar
This thesis presents novel contributions in two primary areas: advancing the efficiency of generative models, particularly normalizing flows, and applying generative models to solv…
Parallel Backpropagation for Inverse of a Convolution with Application to Normalizing Flows
Sandeep Nagar, Girish Varma
The inverse of an invertible convolution is an important operation that comes up in Normalizing Flows, Image Deblurring, etc. The naive algorithm for backpropagation of this operat…
ICPR 2024 Competition on Safe Segmentation of Drive Scenes in Unstructured Traffic and Adverse Weather Conditions
Furqan Ahmed Shaik, Sandeep Nagar, Aiswarya Maturi +7
The ICPR 2024 Competition on Safe Segmentation of Drive Scenes in Unstructured Traffic and Adverse Weather Conditions served as a rigorous platform to evaluate and benchmark state-…