Findings from University of Leeds Update Knowledge of Biomedicine and Biomedical Engineering (A Nonlinear Mapping Approach to Stain Normalization in Digital Histopathology Images Using Image-Specific Color Deconvolution)
By a News Reporter-Staff News Editor at Biotech Week -- Data detailed on Biotechnology have been presented. According to news reporting from Leeds, United Kingdom, by NewsRx journalists, research stated, "Histopathology diagnosis is based on visual examination of the morphology of histological sections under a microscope. With the increasing popularity of digital slide scanners, decision support systems based on the analysis of digital pathology images are in high demand."
The news correspondents obtained a quote from the research from the University of Leeds, "However, computerized decision support systems are fraught with problems that stem from color variations in tissue appearance due to variation in tissue preparation, variation in stain reactivity from different manufacturers/batches, user or protocol variation, and the use of scanners from different manufacturers. In this paper, we present a novel approach to stain normalization in histopathology images. The method is based on nonlinear mapping of a source image to a target image using a representation derived from color deconvolution. Color deconvolution is a method to obtain stain concentration values when the stain matrix, describing how the color is affected by the stain concentration, is given. Rather than relying on standard stain matrices, which may be inappropriate for a given image, we propose the use of a color-based classifier that incorporates a novel stain color descriptor to calculate image-specific stain matrix. In order to demonstrate the efficacy of the proposed stain matrix estimation and stain normalization methods, they are applied to the problem of tumor segmentation in breast histopathology images."
According to the news reporters, the research concluded: "The experimental results suggest that the paradigm of color normalization, as a preprocessing step, can significantly help histological image analysis algorithms to demonstrate stable performance which is insensitive to imaging conditions in general and scanner variations in particular."
For more information on this research see: A Nonlinear Mapping Approach to Stain Normalization in Digital Histopathology Images Using Image-Specific Color Deconvolution. IEEE Transactions on Biomedical Engineering, 2014;61(6):1729-1738. IEEE Transactions on Biomedical Engineering can be contacted at: Ieee-Inst Electrical Electronics Engineers Inc, 445 Hoes Lane, Piscataway, NJ 08855-4141, USA. (Institute of Electrical and Electronics Engineers - www.ieee.org/; IEEE Transactions on Biomedical Engineering - ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=10)
Our news journalists report that additional information may be obtained by contacting A.M. Khan, University of Leeds, Sch Comp, Leeds LS2 9JT, W Yorkshire, United Kingdom. Additional authors for this research include N. Rajpoot, D. Treanor and D. Magee (see also Biotechnology).
Keywords for this news article include: Biotechnology, Leeds, Europe, United Kingdom
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