| Fusion of quantitative image and genomic biomarkers to improve prognosis assessment of early stage lung cancer patients N Emaminejad, W Qian, Y Guan, M Tan, Y Qiu, H Liu, B Zheng IEEE Transactions on Biomedical Engineering 63 (5), 1034-1043, 2015 | 125 | 2015 |
| Standardization in quantitative imaging: a multicenter comparison of radiomic features from different software packages on digital reference objects and patient data sets M McNitt-Gray, S Napel, A Jaggi, SA Mattonen, L Hadjiiski, M Muzi, ... Tomography 6 (2), 118-128, 2020 | 74 | 2020 |
| Reproducibility of lung nodule radiomic features: Multivariable and univariable investigations that account for interactions between CT acquisition and reconstruction parameters N Emaminejad, MW Wahi‐Anwar, GHJ Kim, W Hsu, M Brown, ... Medical physics 48 (6), 2906-2919, 2021 | 22 | 2021 |
| The effects of variations in parameters and algorithm choices on calculated radiomics feature values: initial investigations and comparisons to feature variability across CT … N Emaminejad, M Wahi-Anwar, J Hoffman, GH Kim, MS Brown, ... Medical Imaging 2018: Computer-Aided Diagnosis 10575, 886-895, 2018 | 11 | 2018 |
| Applying a radiomics approach to predict prognosis of lung cancer patients N Emaminejad, S Yan, Y Wang, W Qian, Y Guan, B Zheng Medical imaging 2016: computer-aided diagnosis 9785, 352-358, 2016 | 11 | 2016 |
| Design and implementation of a high‐throughput pipeline for reconstruction and quantitative analysis of CT image data J Hoffman, N Emaminejad, M Wahi‐Anwar, GH Kim, M Brown, S Young, ... Medical physics 46 (5), 2310-2322, 2019 | 6 | 2019 |
| Towards quantitative imaging: stability of fully automated nodule segmentation across varied dose levels and reconstruction parameters in a low-dose ct screening patient cohort MW Wahi-Anwar, N Emaminejad, J Hoffman, GH Kim, MS Brown, ... Medical Imaging 2018: Computer-Aided Diagnosis 10575, 369-374, 2018 | 4 | 2018 |
| A fully-automated, high-throughput reconstruction and analysis pipeline for quantitative imaging in CT J Hoffman, M Wahi-Anwar, N Emaminejad, H Kim, M Brown, ... MEDICAL PHYSICS 44 (6), 3117-3117, 2017 | 2 | 2017 |
| The effects of slice thickness and radiation dose level variations on computer-aided diagnosis (CAD) nodule detection performance in pediatric chest CT scans N Emaminejad, P Lo, S Ghahremani, GH Kim, MS Brown, MF McNitt-Gray Medical Imaging 2017: Computer-Aided Diagnosis 10134, 68-76, 2017 | 2 | 2017 |
| Exploring new quantitative CT image features to improve assessment of lung cancer prognosis N Emaminejad, W Qian, Y Kang, Y Guan, F Lure, B Zheng Medical Imaging 2015: Computer-Aided Diagnosis 9414, 423-434, 2015 | 2 | 2015 |
| Evaluation of correlation between CT image features and ERCC1 protein expression in assessing lung cancer prognosis M Tan, N Emaminejad, W Qian, S Sun, Y Kang, Y Guan, F Lure, B Zheng Medical Imaging 2014: Image Perception, Observer Performance, and Technology …, 2014 | 1 | 2014 |
| Towards Understandable AI in Lung Nodule Detection: Using the Genetic Algorithm for Interpretable, Human-Understandable Optimization of Nodule Candidate Generation in Lung CT … M Wahi-Anwar, N Emaminejad, G Kim, M Brown, M McNitt-Gray MEDICAL PHYSICS 48 (6), 2021 | | 2021 |
| Understanding Variability in Quantitative Imaging and Radiomics: The Use of Different Phantoms in CT to Explore the Effects of Acquisition and Reconstruction Parameters N Emaminejad, M Wahi-Anwar, M McNitt-Gray MEDICAL PHYSICS 48 (6), 2021 | | 2021 |
| A novel physics-based data augmentation approach for improved robust deep learning in medical imaging: lung nodule CAD false positive reduction in low-dose CT environments MW Wahi-Anwar, N Emaminejad, Y Choi, HG Kim, W Hsu, MS Brown, ... Medical Imaging 2021: Physics of Medical Imaging 11595, 89-104, 2021 | | 2021 |
| Computed Tomography Radiomic Features of Lung Nodules: Characterizing Feature Reproducibility Due to Variations in Image Acquisition and Reconstruction Parameters and … N Emaminejad University of California, Los Angeles, 2021 | | 2021 |
| Understanding Reproducibility of Radiomic Features of Lung Nodules Under Heterogenous CT Acquisition and Reconstruction Conditions N Emaminejad, M Wahi-Anwar, G Kim, M Brown, M McNitt-Gray MEDICAL PHYSICS 46 (6), E399-E400, 2019 | | 2019 |
| Expanding Horizons L Conroy, R Jeraj, J Crosby, D Huff, D Mulrow, E Morris, N Emaminejad, ... MEDICAL PHYSICS 46 (6), E308-E308, 2019 | | 2019 |
| Standardization in Quantitative Imaging: A Comparison of Radiomics Feature Values Obtained by Different Software Packages On a Set of Digital Reference Objects M McNitt-Gray, S Napel, J Kalpathy-Cramer, A Jaggi, D Cherezov, ... MEDICAL PHYSICS 46 (6), E400-E400, 2019 | | 2019 |
| Understanding the Impact of Heterogeneous Iterative Reconstruction and Dose Conditions in Low-Dose CT Computer-Aided Detection of Lung Nodules M Wahi-Anwar, N Emaminejad, G Kim, M McNitt-Gray, M Brown MEDICAL PHYSICS 46 (6), E313-E313, 2019 | | 2019 |
| Robustness of Lung Nodule Classification by Radiomic Texture Feature Across CT Acquisition and Reconstruction Parameters N Emaminejad, J Hoffman, M Wahi-Anwar, G Kim, M Brown, ... MEDICAL PHYSICS 45 (6), E514-E515, 2018 | | 2018 |
Michael McNitt-GrayProfessor of Radiology, UCLA School of MedicineVerified email at mednet.ucla.edu
