Technische Universität München (TUM)

Virtualization of Tissue Staining in Digital Pathology Using an Unsupervised Deep Learning Approach (2019) Lahiani A, Gildenblat J, Klaman I, Albarqouni S, Navab N, Klaiman E Conference contribution Quantifying Structural Heterogeneity of Healthy and Cancerous Mitochondria Using a Combined Segmentation and Classification USK-Net (2019) Mishra M, Schmitt S, Zischka H, Strasser M, Navab N, Marr C, Peng T Conference contribution Multi-scale microaneurysms segmentation using embedding triplet loss (2019) Sarhan MH, Albarqouni S, Yigitsoy M, Navab N, Eslami A Conference contribution Multiclass deep active learning for detecting red blood cell subtypes in brightfield microscopy (2019) Sadafi A, Koehler N, Makhro A, Bogdanova A, Navab N, Marr C, Peng T Conference contribution Perceptual embedding consistency for seamless reconstruction of tilewise style transfer (2019) Lahiani A, Navab N, Albarqouni S, Klaiman E Conference contribution Multi-task learning of a deep K-nearest neighbour network for histopathological image classification and retrieval (2019) Peng T, Boxberg M, Weichert W, Navab N, Marr C Conference contribution Graph convolution based attention model for personalized disease prediction (2019) Kazi A, Shekarforoush S, Krishna SA, Burwinkel H, Vivar G, Wiestler B, Kortuem K, et al. Conference contribution Learning interpretable disentangled representations using adversarial VAEs (2019) Sarhan MH, Eslami A, Navab N, Albarqouni S Conference contribution ‘Project & Excite’ Modules for Segmentation of Volumetric Medical Scans (2019) Rickmann AM, Roy AG, Sarasua I, Navab N, Wachinger C Conference contribution 3DQ: Compact Quantized Neural Networks for Volumetric Whole Brain Segmentation (2019) Paschali M, Gasperini S, Roy AG, Fang MYS, Navab N Conference contribution