Perceptual embedding consistency for seamless reconstruction of tilewise style transfer
Lahiani A, Navab N, Albarqouni S, Klaiman E (2019)
Publication Type: Conference contribution
Publication year: 2019
Journal
Publisher: Springer Science and Business Media Deutschland GmbH
Book Volume: 11764 LNCS
Pages Range: 568-576
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Shenzhen, CHN
ISBN: 9783030322380
DOI: 10.1007/978-3-030-32239-7_63
Abstract
Style transfer is a field with growing interest and use cases in deep learning. Recent work has shown Generative Adversarial Networks (GANs) can be used to create realistic images of virtually stained slide images in digital pathology with clinically validated interpretability. Digital pathology images are typically of extremely high resolution, making tilewise analysis necessary for deep learning applications. It has been shown that image generators with instance normalization can cause a tiling artifact when a large image is reconstructed from the tilewise analysis. We introduce a novel perceptual embedding consistency loss significantly reducing the tiling artifact created in the reconstructed whole slide image (WSI). We validate our results by comparing virtually stained slide images with consecutive real stained tissue slide images. We also demonstrate that our model is more robust to contrast, color and brightness perturbations by running comparative sensitivity analysis tests.
Involved external institutions
Germany (DE)How to cite
APA:
Lahiani, A., Navab, N., Albarqouni, S., & Klaiman, E. (2019). Perceptual embedding consistency for seamless reconstruction of tilewise style transfer. In Dinggang Shen, Pew-Thian Yap, Tianming Liu, Terry M. Peters, Ali Khan, Lawrence H. Staib, Caroline Essert, Sean Zhou (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 568-576). Shenzhen, CHN: Springer Science and Business Media Deutschland GmbH.
MLA:
Lahiani, Amal, et al. "Perceptual embedding consistency for seamless reconstruction of tilewise style transfer." Proceedings of the 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019, Shenzhen, CHN Ed. Dinggang Shen, Pew-Thian Yap, Tianming Liu, Terry M. Peters, Ali Khan, Lawrence H. Staib, Caroline Essert, Sean Zhou, Springer Science and Business Media Deutschland GmbH, 2019. 568-576.
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