@inproceedings{7c57a77c6c874f609da8fb06abc5ee1d,
title = "Intelligent spectral signature bio-imaging in vivo for surgical applications",
abstract = "Multi-spectral imaging provides digital images of a scene or object at a large, usually sequential number of wavelengths, generating precise optical spectra at every pixel. We use the term {"}spectral signature{"} for a quantitative plot of optical property variations as a function of wavelengths. We present here intelligent spectral signature bio-imaging methods we developed, including automatic signature selection based on machine learning algorithms and database search-based automatic color allocations, and selected visualization schemes matching these approaches, Using this intelligent spectral signature bio-imaging method, we could discriminate normal and aganglionic colon tissue of the Hirschsprung's disease mouse model with over 95% sensitivity and specificity in various similarity measure methods and various anatomic organs such as parathyroid gland, thyroid gland and pre-tracheal fat in dissected neck of the rat in vivo.",
keywords = "Aganglionosis, Colon, Hirschsprung's disease, Intelligent algorithms, K-means, Multi-spectral, Parathyroid gland, Spectral signature, Thyroid gland",
author = "Jihoon Jeong and Frykman, {Philip K.} and Mark Gaon and Chung, {Alice P.} and Lindsley, {Erik H.} and Hwang, {Jae Y.} and Farkas, {Daniel L.}",
year = "2007",
doi = "10.1117/12.712412",
language = "English",
isbn = "0819465542",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
booktitle = "Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues V",
note = "Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues V ; Conference date: 22-01-2007 Through 24-01-2007",
}