75 citations · 100 across the 16 of their papers we have counts for
16 papers
NeurEPDiff: Neural Operators to Predict Geodesics in Deformation Spaces
Nian Wu, Miaomiao Zhang
This paper presents NeurEPDiff, a novel network to fast predict the geodesics in deformation spaces generated by a well known Euler-Poincaré differential equation (EPDiff). To achi…
MetaMorph: Learning Metamorphic Image Transformation With Appearance Changes
Jian Wang, Jiarui Xing, Jason Druzgal +2
This paper presents a novel predictive model, MetaMorph, for metamorphic registration of images with appearance changes (i.e., caused by brain tumors). In contrast to previous lear…
Geo-SIC: Learning Deformable Geometric Shapes in Deep Image Classifiers
Jian Wang, Miaomiao Zhang
Deformable shapes provide important and complex geometric features of objects presented in images. However, such information is oftentimes missing or underutilized as implicit know…
BDG-Net: Boundary Distribution Guided Network for Accurate Polyp Segmentation
Zihuan Qiu, Zhichuan Wang, Miaomiao Zhang +3
Colorectal cancer (CRC) is one of the most common fatal cancer in the world. Polypectomy can effectively interrupt the progression of adenoma to adenocarcinoma, thus reducing the r…
Hybrid Atlas Building with Deep Registration Priors
Nian Wu, Jian Wang, Miaomiao Zhang +3
Registration-based atlas building often poses computational challenges in high-dimensional image spaces. In this paper, we introduce a novel hybrid atlas building algorithm that fa…
Bayesian Atlas Building with Hierarchical Priors for Subject-specific Regularization
Jian Wang, Miaomiao Zhang
This paper presents a novel hierarchical Bayesian model for unbiased atlas building with subject-specific regularizations of image registration. We develop an atlas construction pr…
Defending Medical Image Diagnostics against Privacy Attacks using Generative Methods
William Paul, Yinzhi Cao, Miaomiao Zhang +1
Machine learning (ML) models used in medical imaging diagnostics can be vulnerable to a variety of privacy attacks, including membership inference attacks, that lead to violations…
Deep Networks to Automatically Detect Late-activating Regions of the Heart
Jiarui Xing, Sona Ghadimi, Mohammad Abdishektaei +3
This paper presents a novel method to automatically identify late-activating regions of the left ventricle from cine Displacement Encoding with Stimulated Echo (DENSE) MR images. W…
Deep Learning for Regularization Prediction in Diffeomorphic Image Registration
Jian Wang, Miaomiao Zhang
This paper presents a predictive model for estimating regularization parameters of diffeomorphic image registration. We introduce a novel framework that automatically determines th…
DeepFLASH: An Efficient Network for Learning-based Medical Image Registration
Jian Wang, Miaomiao Zhang
This paper presents DeepFLASH, a novel network with efficient training and inference for learning-based medical image registration. In contrast to existing approaches that learn sp…
Mixture Probabilistic Principal Geodesic Analysis
Youshan Zhang, Jiarui Xing, Miaomiao Zhang
Dimensionality reduction on Riemannian manifolds is challenging due to the complex nonlinear data structures. While probabilistic principal geodesic analysis~(PPGA) has been propos…
Plug-and-Play Priors for Reconstruction-based Placental Image Registration
Jiarui Xing, Ulugbek Kamilov, Wenjie Wu +2
This paper presents a novel deformable registration framework, leveraging an image prior specified through a denoising function, for severely noise-corrupted placental images. Rece…
Temporal Registration in Application to In-utero MRI Time Series
Ruizhi Liao, Esra A. Turk, Miaomiao Zhang +4
We present a robust method to correct for motion in volumetric in-utero MRI time series. Time-course analysis for in-utero volumetric MRI time series often suffers from substantial…
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…
Temporal Registration in In-Utero Volumetric MRI Time Series
Ruizhi Liao, Esra Turk, Miaomiao Zhang +4
We present a robust method to correct for motion and deformations for in-utero volumetric MRI time series. Spatio-temporal analysis of dynamic MRI requires robust alignment across…