Data fusion of histological and immunohistochemical image data for breast cancer diagnostics using transfer learning
Pradhan P, Köhler K, Guo S, Rosin O, Popp J, Niendorf A, Bocklitz TW (2021)
Publication Type: Conference contribution
Publication year: 2021
Publisher: SciTePress
Pages Range: 495-506
Conference Proceedings Title: ICPRAM 2021 - Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods
Event location: Virtual, Online
ISBN: 9789897584862
Abstract
A combination of histological and immunohistochemical tissue features can offer better breast cancer diagnosis as compared to histological tissue features alone. However, manual identification of histological and immunohistochemical tissue features for cancerous and healthy tissue requires an enormous human effort which delays the breast cancer diagnosis. In this paper, breast cancer detection using the fusion of histological (H&E) and immunohistochemical (PR, ER, Her2 and Ki-67) imaging data based on deep convolutional neural networks (DCNN) was performed. DCNNs, including the VGG network, the residual network and the inception network were comparatively studied. The three DCNNs were trained using two transfer learning strategies. In transfer learning strategy 1, a pre-trained DCNN was used to extract features from the images of five stain types. In transfer learning strategy 2, the images of the five stain types were used as inputs to a pre-trained multi-input DCNN, and the last layer of the multi-input DCNN was optimized. The results showed that data fusion of H&E and IHC imaging data could increase the mean sensitivity at least by 2% depending on the DCNN model and the transfer learning strategy. Specifically, the pre-trained inception and residual networks with transfer learning strategy 1 achieved the best breast cancer detection.
Involved external institutions
Germany (DE)How to cite
APA:
Pradhan, P., Köhler, K., Guo, S., Rosin, O., Popp, J., Niendorf, A., & Bocklitz, T.W. (2021). Data fusion of histological and immunohistochemical image data for breast cancer diagnostics using transfer learning. In Maria De Marsico, Gabriella Sanniti di Baja, Ana Fred (Eds.), ICPRAM 2021 - Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods (pp. 495-506). Virtual, Online: SciTePress.
MLA:
Pradhan, Pranita, et al. "Data fusion of histological and immunohistochemical image data for breast cancer diagnostics using transfer learning." Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2021, Virtual, Online Ed. Maria De Marsico, Gabriella Sanniti di Baja, Ana Fred, SciTePress, 2021. 495-506.
BibTeX: Download