| Digital mammographic tumor classification using transfer learning from deep convolutional neural networks BQ Huynh, H Li, ML Giger Journal of Medical Imaging 3 (3), 034501-034501, 2016 | 628 | 2016 |
| MR imaging radiomics signatures for predicting the risk of breast cancer recurrence as given by research versions of MammaPrint, Oncotype DX, and PAM50 gene assays H Li, Y Zhu, ES Burnside, K Drukker, KA Hoadley, C Fan, SD Conzen, ... Radiology 281 (2), 382-391, 2016 | 511 | 2016 |
| Volumetric texture analysis of breast lesions on contrast‐enhanced magnetic resonance images W Chen, ML Giger, H Li, U Bick, GM Newstead Magnetic Resonance in Medicine: An Official Journal of the International …, 2007 | 410 | 2007 |
| Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA/TCIA data set H Li, Y Zhu, ES Burnside, E Huang, K Drukker, KA Hoadley, C Fan, ... NPJ breast cancer 2, 16012, 2016 | 359 | 2016 |
| Cancerous breast lesions on dynamic contrast-enhanced MR images: computerized characterization for image-based prognostic markers N Bhooshan, ML Giger, SA Jansen, H Li, L Lan, GM Newstead Radiology 254 (3), 680-690, 2010 | 235 | 2010 |
| Using selective withdrawal to coat microparticles I Cohen, H Li, JL Hougland, M Mrksich, SR Nagel Science 292 (5515), 265-267, 2001 | 202 | 2001 |
| Deciphering genomic underpinnings of quantitative MRI-based radiomic phenotypes of invasive breast carcinoma Y Zhu, H Li, W Guo, K Drukker, L Lan, ML Giger, Y Ji Scientific reports 5 (1), 17787, 2015 | 184 | 2015 |
| Exploring nonlinear feature space dimension reduction and data representation in breast CADx with Laplacian eigenmaps and‐SNE AR Jamieson, ML Giger, K Drukker, H Li, Y Yuan, N Bhooshan Medical physics 37 (1), 339-351, 2010 | 178 | 2010 |
| Prediction of clinical phenotypes in invasive breast carcinomas from the integration of radiomics and genomics data W Guo, H Li, Y Zhu, L Lan, S Yang, K Drukker, E Morris, E Burnside, ... Journal of medical imaging 2 (4), 041007-041007, 2015 | 166 | 2015 |
| Catalytic asymmetric dihydroxylation by gold colloids functionalized with self-assembled monolayers H Li, YY Luk, M Mrksich Langmuir 15 (15), 4957-4959, 1999 | 153 | 1999 |
| Computerized texture analysis of mammographic parenchymal patterns of digitized mammograms1 H Li, ML Giger, OI Olopade, A Margolis, L Lan, MR Chinander Academic Radiology 12 (7), 863-873, 2005 | 147 | 2005 |
| A dual‐stage method for lesion segmentation on digital mammograms Y Yuan, ML Giger, H Li, K Suzuki, C Sennett Medical physics 34 (11), 4180-4193, 2007 | 144 | 2007 |
| Computerized analysis of mammographic parenchymal patterns for assessing breast cancer risk: effect of ROI size and location H Li, ML Giger, Z Huo, OI Olopade, L Lan, BL Weber, I Bonta Medical physics 31 (3), 549-555, 2004 | 143 | 2004 |
| Fractal analysis of mammographic parenchymal patterns in breast cancer risk assessment H Li, ML Giger, OI Olopade, L Lan Academic radiology 14 (5), 513-521, 2007 | 127 | 2007 |
| Transfer learning from convolutional neural networks for computer-aided diagnosis: a comparison of digital breast tomosynthesis and full-field digital mammography K Mendel, H Li, D Sheth, M Giger Academic radiology 26 (6), 735-743, 2019 | 109 | 2019 |
| Deep learning in breast cancer risk assessment: evaluation of convolutional neural networks on a clinical dataset of full-field digital mammograms H Li, ML Giger, BQ Huynh, NO Antropova Journal of medical imaging 4 (4), 041304-041304, 2017 | 105 | 2017 |
| A review of explainable and interpretable AI with applications in COVID‐19 imaging JD Fuhrman, N Gorre, Q Hu, H Li, I El Naqa, ML Giger Medical Physics 49 (1), 1-14, 2022 | 99 | 2022 |
| Digital mammography in breast cancer: additive value of radiomics of breast parenchyma H Li, KR Mendel, L Lan, D Sheth, ML Giger Radiology 291 (1), 15-20, 2019 | 96 | 2019 |
| Variation in algorithm implementation across radiomics software JJ Foy, KR Robinson, H Li, ML Giger, H Al-Hallaq, SG Armato III Journal of medical imaging 5 (4), 044505-044505, 2018 | 82 | 2018 |
| Comparison of breast MRI tumor classification using human-engineered radiomics, transfer learning from deep convolutional neural networks, and fusion methods HM Whitney, H Li, Y Ji, P Liu, ML Giger Proceedings of the IEEE 108 (1), 163-177, 2019 | 81 | 2019 |
Maryellen GigerUniversity of ChicagoVerified email at uchicago.edu
