Compressive Sensing in Medical Imaging (MITACS-Fields Conference on the Mathematics of Medical Imaging)

Last week, there was a meeting in Toronto about Conference on Mathematics of Medical Imaging.

 

• Moving the best parts of 1985’s constrained sensing reconstruction to 2011’s compressed sensing reconstruction by Michael Smith,
• What does compressive sensing mean for X-ray CT and comparisons with its MRI application by Emil Sidky
• Compressed Sensing in Cardiac MRI by Mehmet Akcakaya
• Compressive MUSIC for diffuse optical tomography using joint sparsity by Jong Chul Ye
• A Novel Iterative Thresholding Algorithm for Compressed Sensing Reconstruction of Quantitative MRI Parameters from Insufficient Data by Alexey Samsonov

  

Other abstracts related to CS included:

• Compressed Biological Imaging by Elsa Angelini
• A Survey of Compressed Sensing and Applications to Medical Imaging by Justin Romberg
• Potential for Compressed Sensing in Clinical MR Imaging by Richard Frayne
• Application of Temporally Constrained Compressed Sensing for High Spatial and Temporal Resolution Magnetic Resonance Imaging by Julia Velikina