Color normalization for robust evaluation of microscopy images

This paper deals with color normalization of microscopy images of Langerhans islets in order to increase robustness of the islet segmentation to illumination changes. The main application is automatic quantitative evaluation of the islet parameters, useful for determining the feasibility of islet transplantation in diabetes. First, background illumination inhomogeneity is compensated and a preliminary foreground/background segmentation is performed. The color normalization itself is done in either lαβ or logarithmic RGB color spaces, by comparison with a reference image. The color-normalized images are segmented using color-based features and pixel-wise logistic regression, trained on manually labeled images. Finally, relevant statistics such as the total islet area are evaluated in order to determine the success likelihood of the transplantation.

[1]  Sos Agaian,et al.  Iterative local color normalization using fuzzy image clustering , 2013, Defense, Security, and Sensing.

[2]  Erik Reinhard,et al.  Color Transfer between Images , 2001, IEEE Computer Graphics and Applications.

[3]  B. Hering,et al.  2008 Update From the Collaborative Islet Transplant Registry , 2008, Transplantation.

[4]  A. Davison,et al.  Diabetes imaging—quantitative assessment of islets of Langerhans distribution in murine pancreas using extended-focus optical coherence microscopy , 2012, Biomedical optics express.

[5]  Jan Kybic,et al.  Classification of microscopy images of Langerhans islets , 2014, Medical Imaging.

[6]  Fernando Capela e Silva,et al.  Analysis of pancreas histological images for glucose intolerance identificationusing ImageJ—preliminary results , 2013 .

[7]  Ruixia Xu,et al.  Illuminant and gamma comprehensive normalisation in logRGB space , 2003, Pattern Recognit. Lett..

[8]  Peter Buchwald,et al.  Quantification of the Islet Product: Presentation of a Standardized Current Good Manufacturing Practices Compliant System With Minimal Variability , 2011, Transplantation.

[9]  Peter J. Morris,et al.  Islet isolation assessment in man and large animals , 1990, Acta diabetologia latina.

[10]  Peter Girman,et al.  Digital imaging as a possible approach in evaluation of islet yield. , 2003, Cell transplantation.

[11]  T J Fetterhoff,et al.  Morphologic analysis of pancreatic islets automated image analysis. , 1994, Transplantation proceedings.

[12]  J J O'Neil,et al.  Improved assessment of isolated islet tissue volume using digital image analysis. , 1998, Cell transplantation.