Amirhossein Mohammadian Bajgiran
University of California, Los Angeles, Hi-Z Technology (United States)
Papers
2
Total Citations
277
H-Index
2
About
Amirhossein Mohammadian Bajgiran is a leading researcher at the intersection of medical imaging and artificial intelligence, with a primary focus on advancing prostate cancer (PCa) diagnostics. His work centers on developing novel computational methods to overcome the limitations of qualitative interpretation in multi-parametric MRI (mp-MRI). His most impactful contribution, the "FocalNet" framework (2019), is a deep learning model designed for the joint detection of prostate cancer and prediction of Gleason scores directly from mp-MRI scans. This work, which has garnered over 215 citations, directly addresses the critical issue of inter-reader variability in clinical practice. Complementing this AI-driven approach, Bajgiran has also made significant strides in microstructural imaging. His pioneering validation of diffusion-relaxation correlation spectrum imaging (DR-CSI) against whole-mount digital histopathology (2020, 62 citations) provides a crucial link between advanced MRI metrics and actual tissue microstructure. By bridging the gap between non-invasive imaging and histological ground truth, his research is paving the way for more objective, accurate, and personalized diagnosis and risk stratification of prostate cancer.
Research Focus
Key Achievements
Top Papers
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- 2