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ORCIDNastaran Emaminejad
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2020 – today
- 2024
[c5]Shreyas Fadnavis, Chaitanya Parmar, Nastaran Emaminejad, Alvaro Ulloa Cerna, Areez Malik, Mona Selej, Tommaso Mansi, Preston Dunnmon, Tarik Yardibi, Kristopher Standish, Pablo F. Damasceno:
EchoFM: A View-Independent Echocardiogram Model for the Detection of Pulmonary Hypertension. MICCAI (1) 2024: 253-263
2010 – 2019
- 2018
- [c4]M. Wasil Wahi-Anwar, Nastaran Emaminejad, John M. Hoffman, Grace H. Kim, Matthew S. Brown, Michael F. McNitt-Gray:
Towards quantitative imaging: stability of fully-automated nodule segmentation across varied dose levels and reconstruction parameters in a low-dose CT screening patient cohort. Medical Imaging: Computer-Aided Diagnosis 2018: 105751L - 2017
- [c3]Nastaran Emaminejad
, Pechin Lo, Shahnaz Ghahremani, Grace H. Kim, Matthew S. Brown, Michael F. McNitt-Gray:
The effects of slice thickness and radiation dose level variations on computer-aided diagnosis (CAD) nodule detection performance in pediatric chest CT scans. Medical Imaging: Computer-Aided Diagnosis 2017: 101340B - 2016
- [j1]Nastaran Emaminejad, Wei Qian, Yubao Guan, Maxine Tan, Yuchen Qiu, Hong Liu, Bin Zheng:
Fusion of Quantitative Image and Genomic Biomarkers to Improve Prognosis Assessment of Early Stage Lung Cancer Patients. IEEE Trans. Biomed. Eng. 63(5): 1034-1043 (2016) - [c2]Nastaran Emaminejad, Shiju Yan, Yunzhi Wang, Wei Qian, Yubao Guan, Bin Zheng:
Applying a radiomics approach to predict prognosis of lung cancer patients. Medical Imaging: Computer-Aided Diagnosis 2016: 97851E - 2015
- [c1]Nastaran Emaminejad, Wei Qian, Yan Kang, Yubao Guan, Fleming Lure, Bin Zheng:
Exploring new quantitative CT image features to improve assessment of lung cancer prognosis. Medical Imaging: Computer-Aided Diagnosis 2015: 94141M
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