MedShapeNet – a large-scale dataset of 3D medical shapes for computer vision . In Biomedical Engineering / Biomedizinische Technik Volume 70 Issue 1. Li, J., Zhou, Z., Yang, J., Pepe, A., Gsaxner, C., Luijten, G., et al.

Why is the winner the best? . In IEEE/CVF conference on computer vision and Pattern recognition (CVPR) (pp. 19955-19966). Eisenmann, M., Reinke, A.,...,Li, J.,..., et al.

How we won BraTS 2023 Adult Glioma challenge? Just faking it! Enhanced Synthetic Data Augmentation and Model Ensemble for brain tumour segmentation . Brats 2023 First Place. Ferreira, A., Solak, N., Li, J.., Dammann, P., Kleesiek, J., Alves, V. and Egger, J.

The HoloLens in medicine: A systematic review and taxonomy . In Medical Image Analysis,Volume 85, p.102757. Gsaxner, C., Li, J., Pepe, A., et al.

Medical image segmentation in oral-maxillofacial surgery . In Computer-Aided Oral and Maxillofacial Surgery, pp.1-27. Li, J., Erdt, M., Janoos, F., Chang, T.C. and Egger, J.

Inside-Out Instrument Tracking for Surgical Navigation in Augmented Reality . In 27th ACM symposium on virtual reality software and technology, pp. 1-11. Gsaxner, C., Li, J., Pepe, A., Schmalstieg, D. and Egger, J.

Towards clinical applicability and computational efficiency in automatic cranial implant design: An overview of the AutoImplant 2021 cranial implant design challenge . In Medical Image Analysis, Volume 88, August 2023, 102865. Li, J., Ellis, D.G., Kodym, O., Rauschenbach, L., Rieß, et al.

Anatomy Completor: A Multi-class Completion Framework for 3D Anatomy Reconstruction . In International workshop on shape in medical imaging (pp. 1-14). Cham: Springer Nature Switzerland. Li, J., Pepe, A., Luijten, G., Schwarz-Gsaxner, C., et al.

Advancing Healthcare Through Open Science: StudierFenster and MedShapeNet . In AIRoV - The First Austrian Symposium on AI, Robotics, and Vision 25.-27.3.2024, Innsbruck. Gsaxner, C., Luijten, G., Li, J., et al.

Training β-VAE by Aggregating a Learned Gaussian Posterior with a Decoupled Decoder . In Medical Applications with Disentanglements. MAD 2022. Springer, Cham 2022. [arxiv] [Github][Poster] Li, J., Fragemann, J. et al.

Sparse convolutional neural network for high-resolution skull shape completion and shape super-resolution. In Scientific Reports [Demonstration] Li, J., Gsaxner C., Pepe, A. et al.

AutoImplant 2020 -First MICCAI Challenge on Automatic Cranial Implant Design. In IEEE Transactions on Medical Imaging (TMI) 2021. DOI:10.1109/TMI.2021.3077047. [github][Bibtex]
Li, J., Pimentel, P., Szengel, A., Ehlke, M., Lamecker, H., et al.

A Baseline Approach for AutoImplant: The MICCAI 2020 Cranial Implant Design Challenge. In Multimodal Learning for Clinical Decision Support and Clinical Image-Based Procedures, pp. 75-84. Springer, Cham, 2020. [Project Page]
Li, J., Pepe, A., Gsaxner, C., von Campe, G. and Egger, J.

An Online Platform for Automatic Skull Defect Restoration and Cranial Implant Design . In Medical Imaging 2021: Image-Guided Procedures, Robotic Interventions, and Modeling, vol. 11598, p. 115981Q. International Society for Optics and Photonics, 2021. [Project Page]
Li, J., Pepe, A., Gsaxner, C. and Egger, J.

Detection, segmentation, simulation and visualization of aortic dissections: A review. In Medical image analysis (MedIA), 65, p.101773.
Pepe, A*., Li, J* (*Equal contribution), Rolf-Pissarczyk, M., Gsaxner, C., Chen, X., Holzapfel, G.A. and Egger, J

Automatic Skull Defect Restoration and Cranial Implant Generation for Cranioplasty. In Medical image analysis (MedIA) 2021. [Github]
Li, J., von Campe, G., Pepe, A., Gsaxner, C. et al.