Nastaran Emaminejad
Research Assistant
SPIE Involvement:
Author
Area of Expertise:
Medical Imaging , Computer aided diagnosis , Medical Physics , Quantitative image analysis , Machine Learning
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Profile Summary

Nastaran Emaminejad is a PhD candidate in Medical Physics at University of California at Los Angeles under supervision of Dr. Michael Mc-Nitt Gray and Dr. Matthew Brown. Her research interest focuses on quantitative medical imaging. She has been involved in developing and working with common computer aided diagnosis tools by using of machine learning and computer vision in providing precision medicine.
Publications (7)

Proceedings Article | 16 February 2021 Presentation + Paper
Proc. SPIE. 11595, Medical Imaging 2021: Physics of Medical Imaging
KEYWORDS: Computer aided diagnosis and therapy, Imaging systems, Lung, Medical imaging, Data acquisition, Range imaging, Lung cancer

Proceedings Article | 2 March 2018 Paper
Proc. SPIE. 10575, Medical Imaging 2018: Computer-Aided Diagnosis
KEYWORDS: Computer aided diagnosis and therapy, Cancer, Tumors, Denoising, Image acquisition, Feature extraction, Lung, Computed tomography, Reconstruction algorithms, Lung cancer

Proceedings Article | 27 February 2018 Presentation + Paper
Proc. SPIE. 10575, Medical Imaging 2018: Computer-Aided Diagnosis
KEYWORDS: Computer aided diagnosis and therapy, Cancer, Image segmentation, Feature extraction, Lung, Quantitative analysis, Image quality, Computed tomography, Lung cancer

Proceedings Article | 27 March 2017 Paper
Proc. SPIE. 10134, Medical Imaging 2017: Computer-Aided Diagnosis
KEYWORDS: Oncology, Chest, Computer aided diagnosis and therapy, Data modeling, Diagnostics, Lung, Image quality, Solids, Computed tomography, Computer aided design, Radiation effects, CAD systems, Solid modeling

Proceedings Article | 24 March 2016 Paper
Proc. SPIE. 9785, Medical Imaging 2016: Computer-Aided Diagnosis
KEYWORDS: Computer aided diagnosis and therapy, Cancer, Tumors, Surgery, Image segmentation, Image analysis, Lung, Quantitative analysis, Machine learning, Computed tomography, Lung cancer, Computer-aided diagnosis, New and emerging technologies

Showing 5 of 7 publications
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