Paper
26 January 2017 Color separation of H&E stained samples by linearly projecting the RGB representation onto a custom discriminant surface
Paula Andrea Dorado, Raul Celis, Eduardo Romero
Author Affiliations +
Proceedings Volume 10160, 12th International Symposium on Medical Information Processing and Analysis; 101600P (2017) https://doi.org/10.1117/12.2256966
Event: 12th International Symposium on Medical Information Processing and Analysis, 2016, Tandil, Argentina
Abstract
This paper presents a novel color separation method for Hematoxylin-Eosin (H&E) stained Histopathology Images. The whole (R;G;B) space of the input image is projected to a family of surfaces connecting the distributions of a series of [(R + B)2=B;G] planes that divide the cloud of H&E tones. Such projection is then used to cluster both the Hematoxylin and Eosin samples, from where the color basis are then derived. The projection presented herein is more resilient to noise and therefore the separation process is less hampered when the staining properties largely vary. Unlike other normalization methods evaluated by comparing with gold standard images, the power of the method was demonstrated by thresholding the resulting Hematoxylin image with the well-known Otsu's method and the number of detected nuclei was compared with two manually annotated datasets. Despite the simplicity of this approach, the detection sensitivity was 71 % and 67 %, respectively
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Paula Andrea Dorado, Raul Celis, and Eduardo Romero "Color separation of H&E stained samples by linearly projecting the RGB representation onto a custom discriminant surface", Proc. SPIE 10160, 12th International Symposium on Medical Information Processing and Analysis, 101600P (26 January 2017); https://doi.org/10.1117/12.2256966
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KEYWORDS
Clouds

RGB color model

Image segmentation

Tissues

Image processing

Biological research

Gold

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