Search Results for author: Sarah Frisken

Found 9 papers, 2 papers with code

Spatiotemporal Disentanglement of Arteriovenous Malformations in Digital Subtraction Angiography

no code implementations15 Feb 2024 Kathleen Baur, Xin Xiong, Erickson Torio, Rose Du, Parikshit Juvekar, Reuben Dorent, Alexandra Golby, Sarah Frisken, Nazim Haouchine

Although Digital Subtraction Angiography (DSA) is the most important imaging for visualizing cerebrovascular anatomy, its interpretation by clinicians remains difficult.

Anatomy Disentanglement

Learning Expected Appearances for Intraoperative Registration during Neurosurgery

no code implementations3 Oct 2023 Nazim Haouchine, Reuben Dorent, Parikshit Juvekar, Erickson Torio, William M. Wells III, Tina Kapur, Alexandra J. Golby, Sarah Frisken

In contrast to conventional methods, our approach transfers the processing tasks to the preoperative stage, reducing thereby the impact of low-resolution, distorted, and noisy intraoperative images, that often degrade the registration accuracy.

Image Registration

Double-Uncertainty Guided Spatial and Temporal Consistency Regularization Weighting for Learning-based Abdominal Registration

no code implementations6 Jul 2021 Zhe Xu, Jie Luo, Donghuan Lu, Jiangpeng Yan, Sarah Frisken, Jayender Jagadeesan, William Wells III, Xiu Li, Yefeng Zheng, Raymond Tong

Such convention has two limitations: (i) Besides the laborious grid search for the optimal fixed weight, the regularization strength of a specific image pair should be associated with the content of the images, thus the "one value fits all" training scheme is not ideal; (ii) Only spatially regularizing the transformation may neglect some informative clues related to the ill-posedness.

Image Registration

Do Public Datasets Assure Unbiased Comparisons for Registration Evaluation?

no code implementations20 Mar 2020 Jie Luo, Guangshen Ma, Sarah Frisken, Parikshit Juvekar, Nazim Haouchine, Zhe Xu, Yiming Xiao, Alexandra Golby, Patrick Codd, Masashi Sugiyama, William Wells III

In this study, we use the variogram to screen the manually annotated landmarks in two datasets used to benchmark registration in image-guided neurosurgeries.

Image Registration

Are Registration Uncertainty and Error Monotonically Associated

no code implementations21 Aug 2019 Jie Luo, Sarah Frisken, Duo Wang, Alexandra Golby, Masashi Sugiyama, William M. Wells III

Probabilistic image registration (PIR) methods provide measures of registration uncertainty, which could be a surrogate for assessing the registration error.

Image Registration

On the Applicability of Registration Uncertainty

no code implementations14 Mar 2018 Jie Luo, Alireza Sedghi, Karteek Popuri, Dana Cobzas, Miaomiao Zhang, Frank Preiswerk, Matthew Toews, Alexandra Golby, Masashi Sugiyama, William M. Wells III, Sarah Frisken

For probabilistic image registration (PIR), the predominant way to quantify the registration uncertainty is using summary statistics of the distribution of transformation parameters.

Image Registration

Cannot find the paper you are looking for? You can Submit a new open access paper.