My Ph.D. research focuses on computational imaging methods to improve the quality and speed of tomographic imaging. During my Ph.D., I have worked on various research collaborations with Eli Lily, Canadian Light Source, Argonne National Laboratory, General Electric, Northup Grumman, and Air Force Research Laboratory. These collaborations have lead to several publications and open-source software packages.

 Multi-Slice Fusion

Collaboration between Purdue and Eli Lily

Reconstruction results with 90° limited angle views per time-point:

The multi-slice fusion  result does not suffer from major limited-angle artifacts in contrast to FBP and MBIR+4D-MRF.

CodEx: Coded Exposure CT Reconstruction

Collaboration between Purdue and Argonne national laboratory

Separable Models for cone-beam MBIR Reconstruction

Collaboration between Purdue, GE Aviation, Northrop-Grumman, and Air-force Research Laboratory

The proposed separable cone-beam projection operator allows faster computation of tomographic reconstruction due to more efficient computation and improved parallelism and cache efficiency

The proposed efficient tomographic projector allows us to implement model based iterative reconstruction with advanced prior models leading to an improved reconstruction quality

A Model Based Neuron Detection Approach Using Sparse Location Priors