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Forensic visualization of foreign matter in human tissue by near‐infrared spectral imaging: Methodology and data mining strategies
Author(s) -
Lee Eunah,
Kidder Linda H.,
Kalasinsky Victor F.,
Schoppelrei Joseph W.,
Lewis E. Neil
Publication year - 2006
Publication title -
cytometry part a
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.316
H-Index - 90
eISSN - 1552-4930
pISSN - 1552-4922
DOI - 10.1002/cyto.a.20277
Subject(s) - chemical imaging , spectral imaging , near infrared spectroscopy , hyperspectral imaging , materials science , data acquisition , visualization , computer science , biomedical engineering , medical imaging , nuclear magnetic resonance , remote sensing , artificial intelligence , optics , medicine , geology , physics , operating system
Background: Rapidity of data acquisition, high image fidelity and large field of view are of tremendous value when looking for chemical contaminants or for the proverbial “needle in the haystack” – in this case foreign inclusions in histologic sections of biopsy or autopsy tissues. Near infrared chemical imaging is one of three chemical imaging techniques (NIR, MIR and Raman) based on vibrational spectroscopy, and provides distinct technical advantages for this application. Methods: We have chosen to utilize and evaluate near infrared (NIR) imaging for studies of foreign materials in tissue because the experimental configuration is relatively simple, data collection is rapid, and large sample areas can be screened with high image fidelity and spatial resolution. Results: We have shown that NIR imaging can readily find and identify silicone gel inclusions in biological tissue samples. Additionally, preliminary results indicate that spectral signatures in the data set are also potentially sensitive to structural changes in the surrounding tissue that may be induced by the foreign body. Conclusions: NIR chemical imaging is a powerful, non‐destructive tool for localization and identifying foreign contaminants in biological tissue. Preliminary results indicate that NIR imaging is also sensitive enough to differentiate tissue types (perhaps based on collagen structural differences), and provide data on the spatial localization of these components. © 2006 International Society for Analytical Cytology