Alborz Amir-Khalili
Papers
5
Total Citations
84
H-Index
4
About
Alborz Amir-Khalili is a leading researcher in the field of surgical data science, with a primary focus on advancing robot-assisted partial nephrectomy (RAPN) through intelligent image analysis and augmented reality. His work centers on solving critical intraoperative challenges, particularly the automatic segmentation of occluded vasculature and the identification of tumor boundaries. A key contribution is his development of a method that leverages pulsatile motion analysis to segment vessels hidden by tissue, a breakthrough that significantly enhances surgical precision. His research has amassed over 80 citations, with his 2015 paper on automatic segmentation of occluded vasculature being his most cited work (27 citations). Notably, his 2013 study on uncertainty-encoded augmented reality for RAPN demonstrated a novel approach to overlaying critical information onto the surgical view, improving decision-making during tumor resection. Additionally, his work on multi-modal image-guided tumor identification (15 citations) integrates pre- and intra-operative imaging to help surgeons determine optimal resection margins. Amir-Khalili’s contributions are foundational to the development of safer, more effective robotic surgery systems, directly impacting patient outcomes in nephron-sparing procedures.
Research Focus
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Top Papers
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