Computational Insights into Root Canal Treatment: A Survey of Selected Methods in Imaging, Segmentation, Morphological Analysis, and Clinical Management. In Dentistry Journal, Volume 13 Issue 12. Li, J., Bitter, K., et al. [ Featured Cover Paper]

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.