Name: Computational Imaging Science Lab @ UIUC
Type: Organization
Bio: The Computational Imaging Science Lab led by Prof. Mark Anastasio performs research in computational and theoretical image science and emerging imaging methods.
Location: Urbana, IL, USA
Blog: https://anastasio.bioengineering.illinois.edu/
Computational Imaging Science Lab @ UIUC's Projects
Learning invertible generative models from lossy measurements
Codes related to the paper "Attention-Based CNN-BiLSTM for Sleep States Classification of Spatiotemporal Wide-Field Calcium Imaging Data"
BreastPhantom: modified branch for OAT virtual imaging studies
Crown-like Structure Detection and Segmentation in 3D Light-sheet Microscopy Imaging with Mask R-CNN
A collection of python scripts to interact with large datasets on Dataverse
Codes related to the paper "On hallucinations in tomographic imaging"
Codes related to the paper titled "Mining the manifolds of deep generative models for multiple data-consistent solutions of tomographic imaging problems" by Bhadra et al. (2022)
Codes related to paper "Automated sleep stage classification of wide-field calcium imaging data via multiplex visibility graphs and deep learning"
Codes related to the paper "Normalization of optical fluence distribution for three-dimensional functional optoacoustic tomography of the breast"
Code associated with the paper "Prior Image-Constrained Reconstruction using Style-Based Generative Models" accepted to ICML 2021.
Code for post-hoc analyses for DGM evaluation based on stochastic context models (SCM). Accompanies the benchmark datasets publicly available on Harvard Dataverse.
Three dimensional acoustic breast phantoms for USCT studies