Image Quality Evaluation of New Image Reconstruction Methods Applying the Iterative Reconstruction

Learning Iterative Image Reconstruction

Successful image reconstruction requires the recognition of a scene and the generation of a clean image of that scene. We propose to use recurrent neural networks for both analysis and synthesis. The networks have a hierarchical architecture that represents images in multiple scales with different degrees of abstraction. The mapping between these representations is mediated by a local connectio...

Image Reconstruction from Incomplete Data

Image Reconstruction from Incomplete Data

Iterative Breast Tomosynthesis Image Reconstruction

In digital tomosynthesis imaging, multiple projections of an object are obtained along a small range of di↵erent incident angles in order to reconstruct a pseudo-3D representation of the object. In this paper we discuss a mathematical model for polyenergetic digital breast to-mosynthesis image reconstruction that explicitly takes into account various materials composing the object and the polye...

Reconstruction Image Quality Theory

We have developed an image quality theory for reconstruction that we apply to filtered back-projection (FBP) and statistical reconstruction (OSEM) for Single Photon Emission Computed Tomography (SPECT). Quantitative measures of reconstruction performance are given in terms of signal and noise power spectra, SPS and NPS, that we derive from phantom images. This allows evaluating the properties o...