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Proceedings Paper

Digital staining of pathological tissue specimens using spectral transmittance
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Paper Abstract

Staining of tissue specimens is a classical procedure in pathological diagnosis to enhance the contrast between tissue components such that identification and classification of these components can be easily performed. In this paper, a framework for digital staining of pathological specimens using the information derived from the L-band spectral transmittance of various pathological tissue components is introduced, particularly the transformation of a Hematoxylin and Eosin (HE) stained specimen to its Masson-Trichrome (MT) stained counterpart. The digital staining framework involves the classification of tissue components, which are highlighted when the specimen is actually stained with MT stain, e.g. fibrosis, from the HE-stained image; and the linear mapping between specific sets of HE and MT stained transmittance spectra through pseudo-inverse procedure to produce the LxL transformation matrices that will be used to transform the HE stained transmittance to its equivalent MT stained transmittance configuration. To generate the digitally stained image, the decisions of multiple quadratic classifiers are pooled to form the weighting factors for the transformation matrices. Initial results of our experiments on liver specimens show the viability of multispectral imaging (MSI) for the implementation of digital staining in the pathological context.

Paper Details

Date Published: 29 April 2005
PDF: 12 pages
Proc. SPIE 5747, Medical Imaging 2005: Image Processing, (29 April 2005); doi: 10.1117/12.595016
Show Author Affiliations
Pinky A. Bautista, Tokyo Institute of Technology (Japan)
Tokiya Abe, Tokyo Institute of Technology (Japan)
Masahiro Yamaguchi, Tokyo Institute of Technology (Japan)
Akasaka Natural Vision Research Ctr., NICT (Japan)
Yukako Yagi, Univ. of Pittsburgh Medical Ctr. (United States)
Nagaaki Ohyama, Tokyo Institute of Technology (Japan)
Akasaka Natural Vision Research Ctr., NICT (Japan)


Published in SPIE Proceedings Vol. 5747:
Medical Imaging 2005: Image Processing
J. Michael Fitzpatrick; Joseph M. Reinhardt, Editor(s)

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