Open Access Highly Accessed Methodology article

A fast and robust hepatocyte quantification algorithm including vein processing

Tetyana Ivanovska15*, Andrea Schenk2, André Homeyer2, Meihong Deng3, Uta Dahmen3, Olaf Dirsch4, Horst K Hahn12 and Lars Linsen1

Author affiliations

1 Jacobs University, Bremen, Germany

2 Fraunhofer MEVIS, Institute for Medical Image Computing, Bremen, Germany

3 University Hospital, Essen, Germany

4 German Heart Institute, Berlin, Germany

5 Institute of Community Medicine, Ernst-Moritz-Arndt University, Greifswald, Germany

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Citation and License

BMC Bioinformatics 2010, 11:124  doi:10.1186/1471-2105-11-124

Published: 10 March 2010



Quantification of different types of cells is often needed for analysis of histological images. In our project, we compute the relative number of proliferating hepatocytes for the evaluation of the regeneration process after partial hepatectomy in normal rat livers.


Our presented automatic approach for hepatocyte (HC) quantification is suitable for the analysis of an entire digitized histological section given in form of a series of images. It is the main part of an automatic hepatocyte quantification tool that allows for the computation of the ratio between the number of proliferating HC-nuclei and the total number of all HC-nuclei for a series of images in one processing run. The processing pipeline allows us to obtain desired and valuable results for a wide range of images with different properties without additional parameter adjustment. Comparing the obtained segmentation results with a manually retrieved segmentation mask which is considered to be the ground truth, we achieve results with sensitivity above 90% and false positive fraction below 15%.


The proposed automatic procedure gives results with high sensitivity and low false positive fraction and can be applied to process entire stained sections.