Composition-aware spectroscopic tomography

Luke Pfister, Bhargava Rohit Bhargava, Yoram Bresler, P. Scott Carney

Research output: Contribution to journalArticlepeer-review


Chemical imaging provides information about the distribution of chemicals within a target. When combined with structural information about the target, in situ chemical imaging opens the door to applications ranging from tissue classification to industrial process monitoring. The combination of infrared spectroscopy and optical microscopy is a powerful tool for chemical imaging of thin targets. Unfortunately, extending this technique to targets with appreciable depth is prohibitively slow. We combine confocal microscopy and infrared spectroscopy to provide chemical imaging in three spatial dimensions. Interferometricmeasurements are acquired at a small number of focal depths, and images are formed by solving a regularized inverse scattering problem. A low-dimensional signal model is key to this approach: we assume the target comprises a finite number of distinct chemical species. We establish conditions on the constituent spectra and the number of measurements needed for unique recovery of the target. Simulations illustrate imaging of cellular phantoms and sub-wavelength targets from noisy measurements.

Original languageEnglish (US)
Article number115010
JournalInverse Problems
Issue number11
StatePublished - Nov 2020


  • Computational imaging
  • Inverse scattering
  • Spectroscopy
  • Tomographic microscopy
  • Tomography

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Signal Processing
  • Mathematical Physics
  • Computer Science Applications
  • Applied Mathematics


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