Wiest, Roland

The multimodal brain tumor image segmentation benchmark (BRATS)

Menze, B. H., Jakab, A., Bauer, S., Kalpathy-Cramer, J., Farahani, K., Kirby, J., Burren, Y., Porz, N., Slotboom, J., Wiest, R., et al. (2015) · IEEE Transactions on Medical Imaging

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 6,781

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

A survey of MRI-based medical image analysis for brain tumor studies

Bauer, S., Wiest, R., Nolte, L.-P., & Reyes, M. (2013) · Physics in Medicine and Biology

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 1,036

On the interpretability of artificial intelligence in radiology: challenges and opportunities

Reyes, M., Meier, R., Pereira, S., Silva, C. A., Dahlweid, F.-M., Tengg-Kobligk, H. V., Summers, R. M., & Wiest, R. (2020) · Radiology: Artificial Intelligence

Explainable Artificial Intelligence (XAI)Artificial Intelligence in Healthcare and Education

Cited by 484

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

An fMRI study on mental pain and suicidal behavior

Reisch, T., Seifritz, E., Esposito, F., Wiest, R., Valach, L., & Michel, K. (2010) · Journal of Affective Disorders

Suicide and Self-Harm StudiesNeural and Behavioral Psychology Studies

Cited by 173

Neural correlates of sense of agency in motor control: a neuroimaging meta-analysis

Zito, G. A., Wiest, R., & Aybek, S. (2020) · PLOS ONE

Free Will and AgencyMotor Control and Adaptation

Cited by 79

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

Cited by 69

Distinct and shared patterns of brain plasticity during electroconvulsive therapy and treatment as usual in depression: an observational multimodal MRI-study

Bracht, T., Walther, S., Breit, S., Mertse, N., Federspiel, A., Meyer, A., Soravia, L. M., Wiest, R., & Denier, N. (2023) · Translational Psychiatry

Electroconvulsive Therapy StudiesTreatment of Major Depression

Cited by 25