1 citations · 1 across the 1 of their papers we have counts for
4 papers
Deep Information Theoretic Registration
Alireza Sedghi, Jie Luo, Alireza Mehrtash +5
This paper establishes an information theoretic framework for deep metric based image registration techniques. We show an exact equivalence between maximum profile likelihood and m…
Semi-Supervised Deep Metrics for Image Registration
Alireza Sedghi, Jie Luo, Alireza Mehrtash +5
Deep metrics have been shown effective as similarity measures in multi-modal image registration; however, the metrics are currently constructed from aligned image pairs in the trai…
A Feature-Driven Active Framework for Ultrasound-Based Brain Shift Compensation
Jie Luo, Matt Toews, Ines Machado +10
A reliable Ultrasound (US)-to-US registration method to compensate for brain shift would substantially improve Image-Guided Neurological Surgery. Developing such a registration met…
On the Applicability of Registration Uncertainty
Jie Luo, Alireza Sedghi, Karteek Popuri +8
Estimating the uncertainty in (probabilistic) image registration enables, e.g., surgeons to assess the operative risk based on the trustworthiness of the registered image data. If…