7 papers
Deep Image Prototype Learning with Geometric Heat-Kernel Priors
Jiarui Xing, Tal Zeevi, Nian Wu +1
Learning unsupervised representations of medical imaging cohorts can reveal anatomically meaningful prototypes without expert labels, which are often noisy and fail to capture true…
TLRN: Temporal Latent Residual Networks For Large Deformation Image Registration
Nian Wu, Jiarui Xing, Miaomiao Zhang
This paper presents a novel approach, termed {\em Temporal Latent Residual Network (TLRN)}, to predict a sequence of deformation fields in time-series image registration. The chall…
Learning Geodesics of Geometric Shape Deformations From Images
Nian Wu, Miaomiao Zhang
This paper presents a novel method, named geodesic deformable networks (GDN), that for the first time enables the learning of geodesic flows of deformation fields derived from imag…
Unsupervised Cardiac Video Translation Via Motion Feature Guided Diffusion Model
Swakshar Deb, Nian Wu, Frederick H. Epstein +1
This paper presents a novel motion feature guided diffusion model for unpaired video-to-video translation (MFD-V2V), designed to synthesize dynamic, high-contrast cine cardiac magn…
Robust Orthogonal NMF with Label Propagation for Image Clustering
Jingjing Liu, Nian Wu, Xianchao Xiu +1
Non-negative matrix factorization (NMF) is a popular unsupervised learning approach widely used in image clustering. However, in real-world clustering scenarios, most existing NMF…
IGG: Image Generation Informed by Geodesic Dynamics in Deformation Spaces
Nian Wu, Nivetha Jayakumar, Jiarui Xing +1
Generative models have recently gained increasing attention in image generation and editing tasks. However, they often lack a direct connection to object geometry, which is crucial…