Skip to main content
Research article - Peer-reviewed, 2013

Blind Color Decomposition of Histological Images

Gavrilovic, Milan; Azar, Jimmy; Lindblad, Joakim; Wählby, Carolina; Bengtsson, Ewert; Busch, Christer; Carlbom, Ingrid


Cancer diagnosis is based on visual examination under a microscope of tissue sections from biopsies. But whereas pathologists rely on tissue stains to identify morphological features, automated tissue recognition using color is fraught with problems that stem from image intensity variations due to variations in tissue preparation, variations in spectral signatures of the stained tissue, spectral overlap and spatial aliasing in acquisition, and noise at image acquisition. We present a blind method for color decomposition of histological images. The method decouples intensity from color information and bases the decomposition only on the tissue absorption characteristics of each stain. By modeling the charge-coupled device sensor noise, we improve the method accuracy. We extend current linear decomposition methods to include stained tissues where one spectral signature cannot be separated from all combinations of the other tissues' spectral signatures. We demonstrate both qualitatively and quantitatively that our method results in more accurate decompositions than methods based on non-negative matrix factorization and independent component analysis. The result is one density map for each stained tissue type that classifies portions of pixels into the correct stained tissue allowing accurate identification of morphological features that may be linked to cancer.


Blind source separation; gastrointestinal tract; image restoration; microscopy; prostate; quantification

Published in

IEEE Transactions on Medical Imaging
2013, volume: 32, number: 6, pages: 983-994

Authors' information

Gavrilovic, Milan
Uppsala University
Azar, Jimmy
Uppsala University
Lindblad, Joakim
Swedish University of Agricultural Sciences, Centre for Image Analysis
Wählby, Carolina
Uppsala University
Bengtsson, Ewert
Uppsala University
Busch, Christer
Uppsala University
Carlbom, Ingrid
Uppsala University

UKÄ Subject classification

Computer Science
Medical Image Processing
Biomedical Laboratory Science/Technology

Publication Identifiers


URI (permanent link to this page)