Sepideh Shakeri
University of California, Los Angeles, Hi-Z Technology (United States)
Papers
3
Total Citations
312
H-Index
3
About
Sepideh Shakeri is a leading researcher in the application of advanced magnetic resonance imaging (MRI) for prostate cancer diagnosis and characterization. Her work focuses on leveraging multi-parametric MRI (mp-MRI) and novel microstructural imaging techniques to improve non-invasive cancer detection and reduce inter-reader variability. Shakeri’s most impactful contribution is the development of **FocalNet**, a deep learning framework for joint prostate cancer detection and Gleason score prediction in mp-MRI, which has garnered over 215 citations. This work addresses the critical limitation of qualitative interpretation criteria in current clinical practice. She has also pioneered the use of **diffusion-relaxation correlation spectrum imaging (DR-CSI)** at 3-T MRI to probe prostate microstructure, validating her findings against whole-mount digital histopathology in a study cited 62 times. To bridge the gap between in vivo imaging and ground-truth pathology, Shakeri developed a system using patient-specific 3D-printed molds for precise spatial alignment of MRI with histology, a methodological advance foundational to her field. Her research promises to enhance diagnostic accuracy and personalize treatment planning for prostate cancer patients.
Research Focus
Key Achievements
Top Papers
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