13 papers accepted at MICCAI 2019

We are happy to announce that 13 papers of our chair will be presented at the 22nd International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI 2019) in Shenzhen, China, October 13-17, 2019.

With an acceptance rate of approx. 31%, MICCAI is one of the most competitive international meetings in the field. It is based on full paper submissions and double-blind review process.

Congratulations!

2019
	A. Sekuboyina, M. Rempfler, A. Valentinitsch, M. Loeffler, J. Kirschke, B. Menze Probabilistic Point Cloud Reconstructions for Vertebral Shape Analysis Proceedings of the 22th International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI), Shenzen, China, October 2019. (bib)
	M. H. Sarhan, S. Albarqouni, N. Navab, A. Eslami Multi-scale Microaneurysms Segmentation Using Embedding Triplet Loss 22nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Shenzhen, China, 2019 (bib)
	M. Paschali, S. Gasperini, A. Guha Roy, M.Y.-S. Fang, N. Navab 3DQ: Compact Quantized Neural Networks for Volumetric Whole Brain Segmentation The first two authors contributed equally. 22nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Shenzhen 2019. The original publication is available currently online on arXiv and will become available at link.springer.com (bib)
	F. Navarro, S. Shit, I. Ezhov, J. Paetzold, A. Gafita, J. Peeken, S. Combs, B. Menze Shape-Aware Complementary-Task Learning for Multi-Organ Segmentation Proceedings of the 10th International Workshop on Machine Learning in Medical Imaging (MLMI 2019), Shenzhen, China, October 2019. (bib)
	A. Lahiani, N. Navab, S. Albarqouni, E. Klainman Perceptual Embedding Consistency for Seamless Reconstruction of Tilewise Style Transfer 22nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Shenzhen, China, 2019 (bib)
	A. Khakzar, S. Albarqouni, N. Navab Learning Interpretable Features via Adversarially Robust Optimization 22nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Shenzhen, China, 2019 (pre-print version is available online at arXiv) (bib)
	A. Kazi, S. Shekarforoush, S. Krishna, H. Burwinkel, G. Vivar, B. Wiestler, K. Kortüm, A. Ahmadi, S. Albarqouni, N. Navab Graph convolution based attention model for personalized disease prediction 22nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Shenzhen, China, 2019 (bib)
	H. Li, J. Paetzold, A. Sekuboyina, F. Kofler, Jianguo Zhang, J. Kirschke, B. Wiestler, B. Menze DiamondGan: Unified Multi-modal Generative Adversarial Networks for MRI Sequences Synthesis Proceedings of the 22th International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI), Shenzhen, China, October 2019. (bib)
	S. Hariharan, N. Strobel, C. Kaethner, M. Kowarschik, S. Albarqouni, R. Fahrig, N. Navab Learning-based X-ray Image Denoising utilizing Model-based Image Simulations 22nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Shenzhen, China, 2019 (bib)
	I. Ezhov, J. Lipkova, S. Shit, F. Kofler, N. Collomb, B. Lemasson, E. Barbier, B. Menze Neural parameters estimation for brain tumor growth modeling Proceedings of the 22th International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI), Shenzhen, China, October 2019. (bib)
	H. Burwinkel, A. Kazi, G. Vivar, S. Albarqouni, G. Zahnd, N. Navab, A. Ahmadi Adaptive image-feature learning for disease classification using inductive graph networks International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI), Shenzhen, China, 2019 (pre-print version is available online at arXiv) (bib)
	H. Lee, S.T. Kim, J.Lee, Y.M. Ro Realistic Breast Mass Generation through BIRADS Category 22nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Shenzhen, China, 2019 (bib)
	F. Navarro, , M. Günther, , A. Gafita, M. Bieth, G. Tetteh, Jian Wang, S. Weber, M. Eiber qPSMA: Semiautomatic Software for Whole-Body Tumor Burden Assessment in Prostate Cancer Using 68Ga-PSMA11 PET/CT Proceedings of the Journal of Nuclear Medicine (bib)
	F. Navarro, S. Conjeti, F. Tombari, N. Navab Leveraging Web Data for Skin Lesion Classification Proceedings of the Bildverarbeitung für die Medizin 2019 (bib)