Dr. Javier Montoya

Projects

• Web-Based Traffic Prediction Engine for Urban Traffic Simulation / Co-project leader / ongoing
• Novel Data-Driven Models for Robust Ultra-Low-Dose PET Image Reconstruction and CT-Free PET Image Synthesis / Project leader / ongoing
• Synthetic data generation of CoVID-19 CT/X-rays images for enabling fast triage of healthy vs. unhealthy patients / Project leader / completed
• Standardized Data and Modeling for AI-based CoVID-19 Diagnosis Support on CT Scans / Team member / completed
• DIR3CT: Deep Image Reconstruction through X-Ray Projection-based 3D Learning of Computed Tomography Volumes / Team member / completed
• RealScore – Scanning of Real-World Sheet Music for a Digital Music Stand / Team member / completed

Publications

Articles in scientific journal, peer-reviewed

Tuggener, L., Emberger, R., Ghosh, A., Sager, P., Satyawan, Y. P., Montoya, J., Goldschagg, S., Seibold, F., Gut, U., Ackermann, P., Schmidhuber, J., & Stadelmann, T. (2024). Real world music object recognition. Transactions of the International Society for Music Information Retrieval, 7(1), 1–14. https://doi.org/10.5334/tismir.157

Written conference contributions, peer-reviewed

• Cheng, C.-W., Zhao, Y., Cheng, Y., Montoya-Zegarra, J. A., Schönlieb, C.-B., & Aviles-Rivero, A. I. (2025). Implicit U-KAN2.0 : dynamic, efficient and interpretable medical image segmentation [Conference paper]. In J. C. Gee, D. C. Alexander, J. Hong, J. E. Iglesias, C. H. Sudre, A. Venkataraman, P. Golland, J. H. Kim, & J. Park (Eds.), Medical Image Computing and Computer Assisted Intervention – MICCAI 2025: Vol. XI (pp. 304–314). Springer. https://doi.org/10.1007/978-3-032-05141-7_30
• Mandujano-Cornejo, V., & Montoya-Zegarra, J. A. (2022). Polyp2Seg : improved polyp segmentation with vision transformer [Conference paper]. In G. Yang, A. Aviles-Rivero, M. Roberts, & C.-B. Schönlieb (Eds.), Medical Image Understanding and Analysis (pp. 519–534). Springer. https://doi.org/10.1007/978-3-031-12053-4_39
• Amirian, M., Montoya, J., Gruss, J., Stebler, Y. D., Bozkir, A. S., Calandri, M., Schwenker, F., & Stadelmann, T. (2021, October). PrepNet : a convolutional auto-encoder to homogenize CT scans for cross-dataset medical image analysis. Proceedings of CISP-BMEI’21. https://doi.org/10.21256/zhaw-23318

Other publications

• Jing, P., Tang, Y., Cheng, C.-W., Zhang, Z., Yang, L., Lima, T. V., Strobel, K., Leimgruber, A., Aviles-Rivero, A., Yang, G., & Montoya-Zegarra, J. A. (2026). 3D wavelet-based structural priors for controlled diffusion in whole-body low-dose PET denoising. arXiv. https://doi.org/10.48550/arxiv.2601.07093
• Cheng, Y., Cheng, C.-W., Denholm, J., Lima, T., Montoya-Zegarra, J. A., Goodwin, R., Schönlieb, C.-B., & Aviles-Rivero, A. I. (2025). DNA-Prior : unsupervised denoise anything via dual-domain prior. arXiv. https://doi.org/10.48550/arxiv.2511.23124

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