Automatic Detection of Tumor Buds in Pan-Cytokeratin Stained Colorectal Cancer Sections by a Hybrid Image Analysis Approach
| Autor: | Matthias Bergler, Carol Geppert, Susanne Merkel, Arndt Hartmann, David Hartmann, Thomas Wittenberg, Volker Bruns, David Rauber, Malte Kötter, Markus Eckstein, Regine Schneider-Stock, Michaela Benz |
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| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | Digital Pathology ISBN: 9783030239367 ECDP |
| DOI: | 10.1007/978-3-030-23937-4_10 |
| Popis: | This contribution introduces a novel approach to the automatic detection of tumor buds in a digitalized pan-cytokeratin stained colorectal cancer slide. Tumor buds are representing an invasive pattern and are frequently investigated as a new diagnostic factor for measuring the aggressiveness of colorectal cancer. However, counting the number of buds under the microscope in a high power field by eyeballing is a strenuous, lengthy and error-prone task, whereas an automated solution could save time for the pathologists and enhance reproducibility. We propose a new hybrid method that consists of two steps. First possible tumor bud candidates are detected using a chain of classical image processing methods. Afterwards a convolutional deep neural network is applied to filter and reduce the number of false positive candidates detected in the first step. By comparing the automatically detected buds with a gold standard created by manual annotations, we gain a score of 0.977 for precision and 0.934 for sensitivity in our test sets on over 8.000 tumor buds. |
| Databáze: | OpenAIRE |
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