Multimodal image fusion with SIMS: Preprocessing with image registration

Jay Gage Tarolli, Anna Bloom, Nicholas Winograd

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


In order to utilize complementary imaging techniques to supply higher resolution data for fusion with secondary ion mass spectrometry (SIMS) chemical images, there are a number of aspects that, if not given proper consideration, could produce results which are easy to misinterpret. One of the most critical aspects is that the two input images must be of the same exact analysis area. With the desire to explore new higher resolution data sources that exists outside of the mass spectrometer, this requirement becomes even more important. To ensure that two input images are of the same region, an implementation of the insight segmentation and registration toolkit (ITK) was developed to act as a preprocessing step before performing image fusion. This implementation of ITK allows for several degrees of movement between two input images to be accounted for, including translation, rotation, and scale transforms. First, the implementation was confirmed to accurately register two multimodal images by supplying a known transform. Once validated, two model systems, a copper mesh grid and a group of RAW 264.7 cells, were used to demonstrate the use of the ITK implementation to register a SIMS image with a microscopy image for the purpose of performing image fusion.

Original languageEnglish (US)
Pages (from-to)2A311-1-2A311-10
Issue number2
StatePublished - 2016

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Biomaterials
  • Materials Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Physics and Astronomy(all)


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