Conference on Modern Challenges in Imaging
In the Footsteps of Allan MacLeod Cormack
On the Fortieth Anniversary of his Nobel Prize

August 5-9, 2019, Tufts University, Medford, Massachusetts

Since the advent of CT and the pioneering work of Allan Cormack and Godfrey Hounsfield, engineers, mathematicians and physicists have devoted their research in imaging to develop new systems, new architectures, new technologies and new scientific tools in order to address the following, at times contradictory, questions for a range of tomographic modalities:

  • How to obtain better images containing richer information?
  • How to speed the acquisition process and the reconstruction process?
  • How to be cheaper to build and implement?
  • How to be less dangerous to the patient or to the environment?

Answers to these questions has led to a rich set of both technological and mathematical issues, which will be addressed at this conference. In order both to provide an overview of the different aspects and to foster new collaborations, this meeting will gather a diverse collection of practitioners and researchers with interests in a broad range of tomographic modalities to focus on the following topics:

  • X-ray tomography including absorption, coherent scatter, and incoherent scatter.
  • Optical tomography including diffuse, fluorescence molecular, and related modalities.
  • Data diversity arising from the exploitation of multi-energy, multi-spectral, coherent scatter, incoherent scatter and similar data types (including Compton tomography).
  • Machine learning in tomography.
  • The mathematics and algorithms behind tomographic reconstruction.
  • Extraction of time-dependent information (dynamic tomographic problems) for a range of tomographic modalities.
  • Limited view geometries including microlocal reconstruction of singularities, sparse sampling, regularization, dictionary learning, and related approaches.
  • Theoretical underpinnings of tomography including integral geometry and microlocal analysis (the analysis of singularities and artifacts for limited data tomography problems for each modality).
  • Applications in medical, security, and industrial domains.