The multimodal brain tumor image segmentation benchmark (BRATS) BH Menze, A Jakab, S Bauer, J Kalpathy-Cramer, K Farahani, J Kirby, ... IEEE transactions on medical imaging 34 (10), 1993-2024, 2014 | 5712 | 2014 |
The Cancer Imaging Archive (TCIA): maintaining and operating a public information repository K Clark, B Vendt, K Smith, J Freymann, J Kirby, P Koppel, S Moore, ... Journal of digital imaging 26, 1045-1057, 2013 | 4146 | 2013 |
The lung image database consortium (LIDC) and image database resource initiative (IDRI): a completed reference database of lung nodules on CT scans SG Armato III, G McLennan, L Bidaut, MF McNitt‐Gray, CR Meyer, ... Medical physics 38 (2), 915-931, 2011 | 2495 | 2011 |
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 | 2448 | 2017 |
Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ... arXiv preprint arXiv:1811.02629, 2018 | 1851 | 2018 |
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 286, 2017 | 777 | 2017 |
The rsna-asnr-miccai brats 2021 benchmark on brain tumor segmentation and radiogenomic classification U Baid, S Ghodasara, S Mohan, M Bilello, E Calabrese, E Colak, ... arXiv preprint arXiv:2107.02314, 2021 | 569 | 2021 |
MR imaging predictors of molecular profile and survival: multi-institutional study of the TCGA glioblastoma data set DA Gutman, LAD Cooper, SN Hwang, CA Holder, JJ Gao, TD Aurora, ... Radiology 267 (2), 560-569, 2013 | 452 | 2013 |
Monai: An open-source framework for deep learning in healthcare MJ Cardoso, W Li, R Brown, N Ma, E Kerfoot, Y Wang, B Murrey, ... arXiv preprint arXiv:2211.02701, 2022 | 298 | 2022 |
Autosegmentation for thoracic radiation treatment planning: a grand challenge at AAPM 2017 J Yang, H Veeraraghavan, SG Armato III, K Farahani, JS Kirby, ... Medical physics 45 (10), 4568-4581, 2018 | 250 | 2018 |
Outcome prediction in patients with glioblastoma by using imaging, clinical, and genomic biomarkers: focus on the nonenhancing component of the tumor R Jain, LM Poisson, D Gutman, L Scarpace, SN Hwang, CA Holder, ... Radiology 272 (2), 484-493, 2014 | 248 | 2014 |
PROSTATEx Challenges for computerized classification of prostate lesions from multiparametric magnetic resonance images SG Armato III, H Huisman, K Drukker, L Hadjiiski, JS Kirby, N Petrick, ... Journal of Medical Imaging 5 (4), 044501-044501, 2018 | 157 | 2018 |
Genomic mapping and survival prediction in glioblastoma: molecular subclassification strengthened by hemodynamic imaging biomarkers R Jain, L Poisson, J Narang, D Gutman, L Scarpace, SN Hwang, C Holder, ... Radiology 267 (1), 212-220, 2013 | 152 | 2013 |
NCI-ISBI 2013 challenge: automated segmentation of prostate structures N Bloch, A Madabhushi, H Huisman, J Freymann, J Kirby, M Grauer, ... The Cancer Imaging Archive 370 (6), 5, 2015 | 136 | 2015 |
Addition of MR imaging features and genetic biomarkers strengthens glioblastoma survival prediction in TCGA patients M Nicolasjilwan, Y Hu, C Yan, D Meerzaman, CA Holder, D Gutman, ... Journal of Neuroradiology 42 (4), 212-221, 2015 | 133 | 2015 |
LUNGx Challenge for computerized lung nodule classification SG Armato III, K Drukker, F Li, L Hadjiiski, GD Tourassi, RM Engelmann, ... Journal of Medical Imaging 3 (4), 044506-044506, 2016 | 127 | 2016 |
Identifying the best machine learning algorithms for brain tumor segmentation S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ... progression assessment, and overall survival prediction in the BRATS …, 2018 | 120 | 2018 |
The public cancer radiology imaging collections of The Cancer Imaging Archive F Prior, K Smith, A Sharma, J Kirby, L Tarbox, K Clark, W Bennett, T Nolan, ... Scientific data 4 (1), 1-7, 2017 | 115 | 2017 |
Multicenter imaging outcomes study of The Cancer Genome Atlas glioblastoma patient cohort: imaging predictors of overall and progression-free survival P Wangaryattawanich, M Hatami, J Wang, G Thomas, A Flanders, J Kirby, ... Neuro-oncology 17 (11), 1525-1537, 2015 | 114 | 2015 |
Image data sharing for biomedical research—meeting HIPAA requirements for de-identification JB Freymann, JS Kirby, JH Perry, DA Clunie, CC Jaffe Journal of digital imaging 25 (1), 14-24, 2012 | 110 | 2012 |