McKinley, Richard

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Bakas, S., Reyes, M., Jakab, A., Bauer, S., Rempfler, M., Crimi, A., Shinohara, R. T., Berger, C., Ha, S. M., Rozycki, M., et al. (2018) · Apollo - University of Cambridge Repository

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the brats challenge

Bakas, S., Reyes, M., Jakab, A., Bauer, S., Rempfler, M., Crimi, A., Shinohara, R. T., Berger, C., Ha, S. M., Rozycki, M., et al. (2018) · arXiv

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

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Federated learning enables big data for rare cancer boundary detection

Pati, S., Baid, U., Edwards, B., Sheller, M., Wang, S.-H., Reina, G. A., Foley, P., Gruzdev, A., Karkada, D., Davatzikos, C., et al. (2022) · Nature Communications

Privacy-Preserving Technologies in DataBrain Tumor Detection and Classification

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Towards Uncertainty-Assisted Brain Tumor Segmentation and Survival Prediction

Jungo, A., McKinley, R., Meier, R., Knecht, U., Vera, L., Pérez-Beteta, J., Molina-García, D., Pérez-García, V. M., Wiest, R., & Reyes, M. (2018) · Lecture Notes in Computer Science

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

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