CAMP Awards at MICCAI 2018

Once again our students made the difference!

Bastien Bier received the Young Investigator Award for his research work at CAMP Lab in JHU: Bastian Bier, Mathias Unberath, Jan-Nico Zaech, J. Fotouhi, , G. Osgood, N. Navab, A. Maier, X-ray-transform Invariant Anatomical Landmark Detection for Pelvic Trauma Surgery, International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 55 - 63, 2018. The first two authors are joint first authors. (bib) This is the forth consecutive year in which students from CAMP receive the Young Investigator Award.

Abhijit Guha Roy received the student travel award and gave a fantastic oral presentation of his work.

Fernando Navarro was also granted the student travel award.

Dr. Shadi Albarqouni was one of the 26 reviewers to be honored with a reviewer commendation.

Last, but certainly not least, Gerome Vivar received the best paper award in the 2nd Workshop on GRaphs in biomedicAl Image anaLysis (GRAIL).

The awarded papers

2020
	G. Vivar, , A. Zwergal, N. Navab, A. Ahmadi Peri-Diagnostic Decision Support Through Cost-Efficient Feature Acquisition at Test-Time 23nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Lima, Peru, 2020 (bib)
	G. Vivar, A. Kazi, H. Burwinkel, A. Zwergal, N. Navab, A. Ahmadi Simultaneous imputation and disease classification in incomplete medical datasets using Multigraph Geometric Matrix Completion (MGMC) The original version is available online at arXiv. (bib)
2019
	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. 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)
	A. Kazi, S. Shekarforoush, S. Krishna, H. Burwinkel, G. Vivar, K. Kortüm, A. Ahmadi, S. Albarqouni, N. Navab InceptionGCN : Receptive Field Aware Graph Convolutional Network for Disease Prediction (Oral) Proceedings of International Conference on Information Processing in Medical Imaging (IPMI), Hong Kong, 2019 (bib)
	G. Vivar, H. Burwinkel, A. Kazi, A. Zwergal, N. Navab, A. Ahmadi Multi-modal Graph Fusion for Inductive Disease Classification in Incomplete Datasets The original version is available online at arXiv. (bib)
2018
	G. Vivar, A. Zwergal, N. Navab, A. Ahmadi Multi-modal Disease Classification in Incomplete Datasets Using Geometric Matrix Completion. Proceedings of MICCAI Workshop on Graphs in Biomedical Image Analysis, Granada, Spain, September 2018. (bib)

Guha Roy, A., Navab, N. and Wachinger, C. (2018). Concurrent Spatial and Channel Squeeze & Excitation in Fully Convolutional Networks. In Med. Image Comput., Comp. Assist. Interv. (MICCAI), 2018. (Oral Presentation, Top 4% of submissions)

Navarro, F., Conjeti, S., Tombari, F. and Navab, N. (2018, March). Webly Supervised Learning for Skin Lesion Classification. In Med. Image Comput., Comp. Assist. Interv. (MICCAI), 2018.