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Results: 9
Number of items: 9
  • Open Access
    de Vente, C. W. (2025). Towards robust deep learning for medical imaging: Applications in ophthalmology and radiology. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    de Vente, C., Valmaggia, P., Hoyng, C. B., Holz, F. G., Islam, M. M., Klaver, C. C. W., Boon, C. J. F., Schmitz-Valckenberg, S., Tufail, A., Saßmannshausen, M., & Sánchez, C. I. (2024). Generalizable Deep Learning for the Detection of Incomplete and Complete Retinal Pigment Epithelium and Outer Retinal Atrophy: A MACUSTAR Report. Translational Vision Science and Technology, 13(9), Article 11. https://doi.org/10.1167/tvst.13.9.11
  • Open Access
    Islam, M. M., de Vente, C., Liefers, B., Klaver, C., Bekkers, E. J., & Sánchez, C. I. (2024). Uncertainty-aware retinal layer segmentation in OCT through probabilistic signed distance functions. Proceedings of Machine Learning Research, 250, 672-693. https://doi.org/10.48550/arXiv.2412.04935
  • Open Access
    de Vente, C., van Ginneken, B., Hoyng, C. B., Klaver, C. C. W., & Sánchez, C. I. (2024). Uncertainty-aware multiple-instance learning for reliable classification: Application to optical coherence tomography. Medical Image Analysis, 97, Article 103259. https://doi.org/10.1016/j.media.2024.103259
  • de Vente, C., & Sá‎nchez, C. I. (2022). Rotterdam EyePACS AIROGS Lite development and test set [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7178671
  • de Vente, C., & Sá‎nchez, C. I. (2022). Rotterdam EyePACS AIROGS Lite development set [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7056954
  • de Vente, C., Boulogne, L. H., Venkadesh, K. V., Sital, C., Lessmann, N., Jacobs, C., Sanchez, C. I., & van Ginneken, B. (2022). Automated COVID-19 Grading With Convolutional Neural Networks in Computed Tomography Scans: A Systematic Comparison. IEEE transactions on artificial intelligence, 3(2), 129-138. https://doi.org/10.1109/TAI.2021.3115093
  • Open Access
    Schwartz, R., Khalid, H., Liakopoulos, S., Ouyang, Y., de Vente, C., González-Gonzalo, C., Lee, A. Y., Guymer, R., Chew, E. Y., Egan, C., Wu, Z., Kumar, H., Farrington, J., Müller, P. L., Sánchez, C. I., & Tufail, A. (2022). A Deep Learning Framework for the Detection and Quantification of Reticular Pseudodrusen and Drusen on Optical Coherence Tomography. Translational vision science & technology, 11(12), Article 3. https://doi.org/10.1167/tvst.11.12.3
  • Lessmann, N., Sánchez, C. I., Beenen, L., Boulogne, L. H., Brink, M., Calli, E., Charbonnier, J.-P., Dofferhoff, T., van Everdingen, W. M., Gerke, P. K., Geurts, B., Gietema, H. A., Groeneveld, M., van Harten, L., Hendrix, N., Hendrix, W., Huisman, H. J., Išgum, I., Jacobs, C., ... van Ginneken, B. (2021). Automated Assessment of COVID-19 Reporting and Data System and Chest CT Severity Scores in Patients Suspected of Having COVID-19 Using Artificial Intelligence. Radiology, 298(1), E18-E28. https://doi.org/10.1148/radiol.2020202439
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