Despite many efforts, some tissue changes, associated with diseases such as cancer, remain beyond the detection limit of OCT. A technique which would allow extraction of information regarding these unresolvable features from the OCT signal could prove a very powerful diagnostic tool. This manuscript presents such a procedure. It begins with the separation of the signal in resolvable and unresolvable components using wavelet decomposition. Subsequently, the power spectral density of the unresolvable part is determined with autoregressive spectral estimation. Statistical analysis is then employed to extract information regarding the uresolvable, but diagnostically significant, scatterers in tissue. These characteristics could considerably improve the clinical utility of OCT.

Date Published: 7 October 2005
PDF: 8 pages
Proc. SPIE 5861, Optical Coherence Tomography and Coherence Techniques II, 586109 (7 October 2005); doi: 10.1117/12.632967

Published in SPIE Proceedings Vol. 5861:
Optical Coherence Tomography and Coherence Techniques II
Wolfgang Drexler, Editor(s)