Bilello, Michel

Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features

Bakas, S., Akbari, H., Sotiras, A., Bilello, M., Rozycki, M., Kirby, J. S., Freymann, J. B., Farahani, K., & Davatzikos, C. (2017) · Scientific Data

Radiomics and Machine Learning in Medical ImagingBrain Tumor Detection and Classification

Cited by 3,049

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

Cited by 1,441

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

Cited by 1,441

The Medical Segmentation Decathlon

Antonelli, M., Reinke, A., Bakas, S., Farahani, K., Kopp-Schneider, A., Landman, B. A., Litjens, G., Menze, B., Ronneberger, O., Summers, R. M., et al. (2022) · Nature Communications

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 1,384

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

Cited by 394

Segmentation Labels for the Pre-operative Scans of the TCGA-GBM collection

Bakas, S., Akbari, H., Sotiras, A., Bilello, M., Rozycki, M., Kirby, J., Freymann, J., Farahani, K., & Davatzikos, C. (2017) · The Cancer Imaging Archive

Brain Tumor Detection and ClassificationRadiomics and Machine Learning in Medical Imaging

Cited by 316

Segmentation Labels for the Pre-operative Scans of the TCGA-LGG collection

Bakas, S., Akbari, H., Sotiras, A., Bilello, M., Rozycki, M., Kirby, J., Freymann, J., Farahani, K., & Davatzikos, C. (2017) · The Cancer Imaging Archive

Brain Tumor Detection and ClassificationRadiomics and Machine Learning in Medical Imaging

Cited by 290

Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome

Davatzikos, C., Rathore, S., Bakas, S., Pati, S., Bergman, M., Kalarot, R., Sridharan, P., Gastounioti, A., Jahani, N., Cohen, E., et al. (2018) · Journal of Medical Imaging

Radiomics and Machine Learning in Medical ImagingMRI in cancer diagnosis

Cited by 204

Brain extraction on MRI scans in presence of diffuse glioma: Multi-institutional performance evaluation of deep learning methods and robust modality-agnostic training

Thakur, S., Doshi, J., Pati, S., Rathore, S., Sako, C., Bilello, M., Ha, S. M., Shukla, G., Flanders, A., Kotrotsou, A., et al. (2020) · NeuroImage

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 84

Brain Cancer Imaging Phenomics Toolkit (brain-CaPTk): An Interactive Platform for Quantitative Analysis of Glioblastoma

Rathore, S., Bakas, S., Pati, S., Akbari, H., Kalarot, R., Sridharan, P., Rozycki, M., Bergman, M., Tunc, B., Verma, R., et al. (2018) · Lecture Notes in Computer Science

Radiomics and Machine Learning in Medical ImagingBrain Tumor Detection and Classification

Cited by 57

The federated tumor segmentation (FeTS) tool: an open-source solution to further solid tumor research

Pati, S., Baid, U., Edwards, B., Sheller, M. J., Foley, P., Anthony Reina, G., Thakur, S., Sako, C., Bilello, M., Davatzikos, C., et al. (2022) · Physics in Medicine & Biology

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 51

Cancer Imaging Phenomics via CaPTk: Multi-Institutional Prediction of Progression-Free Survival and Pattern of Recurrence in Glioblastoma

Fathi Kazerooni, A., Akbari, H., Shukla, G., Badve, C., Rudie, J. D., Sako, C., Rathore, S., Bakas, S., Pati, S., Singh, A., et al. (2020) · JCO Clinical Cancer Informatics

Radiomics and Machine Learning in Medical ImagingGlioma Diagnosis and Treatment

Cited by 39