activity
20162018
most citedBayesian Nonparametric Poisson-Process Allocation for Time-Sequence Modeling

6 citations · 11 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2018★ 3 cited

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…

stat.ML2018★ 1 cited

Variational Inference for Gaussian Process with Panel Count Data

Hongyi Ding, Young Lee, Issei Sato +1

We present the first framework for Gaussian-process-modulated Poisson processes when the temporal data appear in the form of panel counts. Panel count data frequently arise when ex…

cs.CV2017★ 1 cited

Misdirected Registration Uncertainty

Jie Luo, Karteek Popuri, Dana Cobzas +3

Being a task of establishing spatial correspondences, medical image registration is often formalized as finding the optimal transformation that best aligns two images. Since the tr…

stat.ML2017★ 6 cited

Bayesian Nonparametric Poisson-Process Allocation for Time-Sequence Modeling

Hongyi Ding, Mohammad Emtiyaz Khan, Issei Sato +1

Analyzing the underlying structure of multiple time-sequences provides insights into the understanding of social networks and human activities. In this work, we present the \emph{B…

cs.CV2016

Reinterpreting the Transformation Posterior in Probabilistic Image Registration

Jie Luo, Karteek Popuri, Dana Cobzas +2

Probabilistic image registration methods estimate the posterior distribution of transformation. The conventional way of interpreting the transformation posterior is to use the mode…