9 citations · 23 across the 15 of their papers we have counts for
8 papers · 1 filter
A Speech-to-Video Synthesis Approach Using Spatio-Temporal Diffusion for Vocal Tract MRI
Paula Andrea Pérez-Toro, Tomás Arias-Vergara, Fangxu Xing +9
Understanding the relationship between vocal tract motion during speech and the resulting acoustic signal is crucial for aided clinical assessment and developing personalized treat…
Treatment-wise Glioblastoma Survival Inference with Multi-parametric Preoperative MRI
Xiaofeng Liu, Nadya Shusharina, Helen A Shih +3
In this work, we aim to predict the survival time (ST) of glioblastoma (GBM) patients undergoing different treatments based on preoperative magnetic resonance (MR) scans. The perso…
Incremental Learning for Heterogeneous Structure Segmentation in Brain Tumor MRI
Xiaofeng Liu, Helen A. Shih, Fangxu Xing +3
Deep learning (DL) models for segmenting various anatomical structures have achieved great success via a static DL model that is trained in a single source domain. Yet, the static…
Memory Consistent Unsupervised Off-the-Shelf Model Adaptation for Source-Relaxed Medical Image Segmentation
Xiaofeng Liu, Fangxu Xing, Georges El Fakhri +1
Unsupervised domain adaptation (UDA) has been a vital protocol for migrating information learned from a labeled source domain to facilitate the implementation in an unlabeled heter…
Variational Inference for Quantifying Inter-observer Variability in Segmentation of Anatomical Structures
Xiaofeng Liu, Fangxu Xing, Thibault Marin +2
Lesions or organ boundaries visible through medical imaging data are often ambiguous, thus resulting in significant variations in multi-reader delineations, i.e., the source of ale…
Adversarial Unsupervised Domain Adaptation with Conditional and Label Shift: Infer, Align and Iterate
Xiaofeng Liu, Zhenhua Guo, Site Li +5
In this work, we propose an adversarial unsupervised domain adaptation (UDA) approach with the inherent conditional and label shifts, in which we aim to align the distributions w.r…