| Advancing the cancer genome atlas glioma MRI collections with expert segmentation labels and radiomic features S Bakas, H Akbari, A Sotiras, M Bilello, M Rozycki, JS Kirby, JB Freymann, ... Scientific data 4 (1), 1-13, 2017 | 2705 | 2017 |
| Segmentation labels and radiomic features for the pre-operative scans of the TCGA-LGG collection S Bakas, H Akbari, A Sotiras, M Bilello, M Rozycki, J Kirby, J Freymann, ... The Cancer Imaging Archive, https://doi.org/10.7937/K9/TCIA.2017.GJQ7R0EF …, 2017 | 818 | 2017 |
| Imaging patterns predict patient survival and molecular subtype in glioblastoma via machine learning techniques L Macyszyn, H Akbari, JM Pisapia, X Da, M Attiah, V Pigrish, Y Bi, S Pal, ... Neuro-oncology 18 (3), 417-425, 2015 | 317 | 2015 |
| Hyperspectral imaging and quantitative analysis for prostate cancer detection H Akbari, LV Halig, DM Schuster, A Osunkoya, V Master, PT Nieh, ... Journal of biomedical optics 17 (7), 076005-076005, 2012 | 304 | 2012 |
| Cancer detection using infrared hyperspectral imaging H Akbari, K Uto, Y Kosugi, K Kojima, N Tanaka Cancer science 102 (4), 852-857, 2011 | 263 | 2011 |
| Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome C Davatzikos, S Rathore, S Bakas, S Pati, M Bergman, R Kalarot, ... Journal of medical imaging 5 (1), 011018-011018, 2018 | 216 | 2018 |
| Detection and analysis of the intestinal ischemia using visible and invisible hyperspectral imaging H Akbari, Y Kosugi, K Kojima, N Tanaka IEEE Transactions on Biomedical Engineering 57 (8), 2011-2017, 2010 | 213 | 2010 |
| Comparative evaluation of registration algorithms in different brain databases with varying difficulty: results and insights Y Ou, H Akbari, M Bilello, X Da, C Davatzikos Medical Imaging, IEEE Transactions on 33 (10), 2039-2065, 2014 | 196 | 2014 |
| Radiomic MRI signature reveals three distinct subtypes of glioblastoma with different clinical and molecular characteristics, offering prognostic value beyond IDH1 S Rathore, H Akbari, M Rozycki, KG Abdullah, MLP Nasrallah, ZA Binder, ... Scientific reports 8 (1), 5087, 2018 | 174 | 2018 |
| Epidermal growth factor receptor extracellular domain mutations in glioblastoma present opportunities for clinical imaging and therapeutic development ZA Binder, AH Thorne, S Bakas, EP Wileyto, M Bilello, H Akbari, ... Cancer cell 34 (1), 163-177. e7, 2018 | 170 | 2018 |
| Imaging surrogates of infiltration obtained via multiparametric imaging pattern analysis predict subsequent location of recurrence of glioblastoma H Akbari, L Macyszyn, X Da, M Bilello, RL Wolf, M Martinez-Lage, G Biros, ... Neurosurgery 78 (4), 572-580, 2016 | 158 | 2016 |
| Radiomic signature of infiltration in peritumoral edema predicts subsequent recurrence in glioblastoma: implications for personalized radiotherapy planning S Rathore, H Akbari, J Doshi, G Shukla, M Rozycki, M Bilello, R Lustig, ... Journal of medical imaging 5 (2), 021219-021219, 2018 | 142 | 2018 |
| Combining generative models for multifocal glioma segmentation and registration D Kwon, RT Shinohara, H Akbari, C Davatzikos Medical Image Computing and Computer-Assisted Intervention–MICCAI 2014: 17th …, 2014 | 130 | 2014 |
| In vivo evaluation of EGFRvIII mutation in primary glioblastoma patients via complex multiparametric MRI signature H Akbari, S Bakas, JM Pisapia, MLP Nasrallah, M Rozycki, ... Neuro-oncology 20 (8), 1068-1079, 2018 | 117 | 2018 |
| GLISTRboost: combining multimodal MRI segmentation, registration, and biophysical tumor growth modeling with gradient boosting machines for glioma segmentation S Bakas, K Zeng, A Sotiras, S Rathore, H Akbari, B Gaonkar, M Rozycki, ... BrainLes 2015, 144-155, 2015 | 115 | 2015 |
| Segmentation labels and radiomic features for the pre-operative scans of the TCGA-GBM collection S Bakas, H Akbari, A Sotiras, M Bilello, M Rozycki, J Kirby, J Freymann, ... The Cancer Imaging Archive, https://doi.org/10.7937/K9/TCIA.2017.KLXWJJ1Q 9 …, 2017 | 107* | 2017 |
| Pattern analysis of dynamic susceptibility contrast-enhanced MR imaging demonstrates peritumoral tissue heterogeneity H Akbari, L Macyszyn, X Da, RL Wolf, M Bilello, R Verma, DM O’Rourke, ... Radiology 273 (2), 502-510, 2014 | 107 | 2014 |
| In Vivo Detection of EGFRvIII in Glioblastoma via Perfusion Magnetic Resonance Imaging Signature Consistent with Deep Peritumoral Infiltration: The ϕ-Index S Bakas, H Akbari, J Pisapia, M Martinez-Lage, M Rozycki, S Rathore, ... Clinical Cancer Research 23 (16), 4724-4734, 2017 | 99 | 2017 |
| The University of Pennsylvania glioblastoma (UPenn-GBM) cohort: advanced MRI, clinical, genomics, & radiomics S Bakas, C Sako, H Akbari, M Bilello, A Sotiras, G Shukla, JD Rudie, ... Scientific data 9 (1), 453, 2022 | 88 | 2022 |
| Histopathology‐validated machine learning radiographic biomarker for noninvasive discrimination between true progression and pseudo‐progression in glioblastoma H Akbari, S Rathore, S Bakas, MLP Nasrallah, G Shukla, E Mamourian, ... Cancer 126 (11), 2625-2636, 2020 | 88 | 2020 |