Akbari, Hamed

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

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

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

GLISTRboost: Combining Multimodal MRI Segmentation, Registration, and Biophysical Tumor Growth Modeling with Gradient Boosting Machines for Glioma Segmentation

Bakas, S., Zeng, K., Sotiras, A., Rathore, S., Akbari, H., Gaonkar, B., Rozycki, M., Pati, S., & Davatzikos, C. (2016) · Lecture Notes in Computer Science

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 101

The Cancer Imaging Phenomics Toolkit (CaPTk): Technical Overview

Pati, S., Singh, A., Rathore, S., Gastounioti, A., Bergman, M., Ngo, P., Ha, S. M., Bounias, D., Minock, J., Murphy, G., et al. (2020) · Lecture Notes in Computer Science

Radiomics and Machine Learning in Medical ImagingMedical Image Segmentation Techniques

Cited by 94

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

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

Artificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 2: recommendations for standardisation, validation, and good clinical practice

Bakas, S., Vollmuth, P., Galldiks, N., Booth, T. C., Aerts, H. J. W. L., Bi, W. L., Wiestler, B., Tiwari, P., Pati, S., Baid, U., et al. (2024) · The Lancet Oncology

Artificial Intelligence in Healthcare and EducationRadiomics and Machine Learning in Medical Imaging

Cited by 36