Reflectivity tomography using temporally truncated data

Mark A. Anastasio, Yu Zou, Xiaochuan Pan

Research output: Contribution to journalConference articlepeer-review


Reflectivity tomography is an imaging technique that aims to reconstruct a function that describes the reflectivity of an inhomogeneous object. Conventional reconstruction algorithms require that backscattered data be measured for all time 0 ≤ t < ∞ and at all source-receiver locations residing on a circle that encloses the object to be imaged. In this work, we examine the reconstruction problem using backscattered data that is temporally truncated. We reveal that, under certain conditions, an exact image can be reconstructed using temporally truncated data. We numerically validate our theoretical assertions.

Original languageEnglish (US)
Pages (from-to)921-922
Number of pages2
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
StatePublished - Dec 1 2002
Externally publishedYes
EventProceedings of the 2002 IEEE Engineering in Medicine and Biology 24th Annual Conference and the 2002 Fall Meeting of the Biomedical Engineering Society (BMES / EMBS) - Houston, TX, United States
Duration: Oct 23 2002Oct 26 2002


  • Reflectivity tomography
  • Tomographic reconstruction

ASJC Scopus subject areas

  • Bioengineering


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