We are happy to announce that 13 papers of our chair will be presented at the 24rd International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI 2021) in Strasbourg, France, September 27 - October 1st, 2021. Due to the COVID situation, the conference is going to be held virtually this year.
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!
Zapaishchykova, A.; Dreizin, D.; Li, Z.; Wu, J.; Roohi, S.; Unberath, A.: An Interpretable Approach to Automated Severity Scoring in Pelvic Trauma. arXiv preprint arXiv:2105.10238, 2021
Tirindelli, M.; Eilers, C.; Simson, W.; Paschali, M.; Azampour, M.; Navab, N.: Rethinking Ultrasound Augmentation: A Physics-Inspired Approach. arXiv preprint arXiv:2105.02188, 2021
Seibold, M.; Hoch, A.; Suter, D.; Farshad, M.; Zing, P.; Navab, N.: Acoustic-based Spatio-temporal Learning for Press-fit Evaluation of Femoral Stem Implants, 2021
Maier, H.; Faghihroohi, S.; Navab, N.: A line to align: Deep dynamic time warping for retinal OCT segmentation, 2021
Kim, S.; Goli, L.; Paschali, M.; Khakzar, A.; Keicher, M.; Czempiel, T.; Burian, E.; Braren, R.; Navab, N.; Wendler, T.: Longitudinal Quantitative Assessment of COVID-19 Infection Progression from Chest CTs. arXiv preprint arXiv:2103.07240, 2021
Khakzar, A.; Musatian, S.; Buchberger, J.; Quiroz, I.; Pinger, N.; Baselizadeh, S.; Kim, S.; Navab, N.: Towards Semantic Interpretation of Thoracic Disease and COVID-19 Diagnosis Models. arXiv preprint arXiv:2104.02481, 2021
Khakzar, A.; Zhang, Y.; Mansour, W.; Cai, Y.; Li, Y.; Zhang, Y.; Kim, S.; Navab, N.: Explaining COVID-19 and Thoracic Pathology Model Predictions by Identifying Informative Input Features. arXiv preprint arXiv:2104.00411, 2021
Karaoglu, M.; Brasch, N.; Stollenga, M.; Wien, W.; Navab, N.; Tombari, F.; Ladikos, A.: Adversarial Domain Feature Adaptation for Bronchoscopic Depth Estimation, 2021
Kalia, M.; Aleef, T.; Navab, N.; Salcudean, S.; Black, P.: Co-Generation and Segmentation for Generalized Surgical Instrument Segmentation on Unlabelled Data. arXiv preprint arXiv:2103.09276, 2021
Ghorbani, M.; Bahrami, M.; Kazi, A.; Baghshah, M.; Rabiee, H.; Navab, N.: GKD: Semi-supervised Graph Knowledge Distillation for Graph-Independent Inference. arXiv preprint arXiv:2104.03597, 2021
Czempiel, T.; Paschali, M.; Kim, S.; Ostler, D.; Busam, B.; Navab, N.: OperA: Attention-Regularized Transformers for Surgical Phase Recognition. arXiv preprint arXiv:2103.03873, 2021
Bukas, C.; Jian, B.; Rodriguez, L.; Benetti, F.; Rühling, S.; Sekuboyina, A.; Gempt, J.; Kirschke, J.; Piraud, M.; Oberreuter, J.; Navab, N.; Wendler, T.: Patient-specific virtual spine straightening and vertebra inpainting: An automatic framework for osteoplasty planning. arXiv preprint arXiv:2103.07279, 2021
Bdair, T.; Navab, N.; Albarqouni, S.: FedPerl: Semi-Supervised Peer Learning for Skin Lesion Classification. arXiv preprint arXiv:2103.03703, 2021
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