% Encoding: UTF-8 @COMMENT{BibTeX export based on data in FAU CRIS: https://cris.fau.de/} @COMMENT{For any questions please write to cris-support@fau.de} @inproceedings{faucris.222063048, abstract = {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.}, address = {Cham}, author = {Bergler, Matthias and Benz, Michaela and Rauber, David and Hartmann, David and Kötter, Malte and Eckstein, Markus and Schneider-Stock, Regine and Hartmann, Arndt and Merkel, Susanne and Bruns, Volker and Wittenberg, Thomas and Geppert, Carol}, booktitle = {Digital Pathology}, date = {2019-04-10/2019-04-13}, doi = {10.1007/978-3-030-23937-4_10}, editor = {Reyes-Aldasoro CC, Janowczyk A, Veta M, Bankhead P, Sirinukunwattana K}, faupublication = {yes}, isbn = {978-3-030-23937-4}, pages = {83--90}, peerreviewed = {Yes}, publisher = {Springer International Publishing}, title = {{Automatic} {Detection} of {Tumor} {Buds} in {Pan}-{Cytokeratin} {Stained} {Colorectal} {Cancer} {Sections} by a {Hybrid} {Image} {Analysis} {Approach}}, url = {https://link.springer.com/chapter/10.1007/978-3-030-23937-4_10}, venue = {Warwick , UK}, year = {2019} }