25 citations · 128 across the 49 of their papers we have counts for
10 papers · 1 filter
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…
Unsupervised Domain Adaptation for Segmentation with Black-box Source Model
Xiaofeng Liu, Chaehwa Yoo, Fangxu Xing +3
Unsupervised domain adaptation (UDA) has been widely used to transfer knowledge from a labeled source domain to an unlabeled target domain to counter the difficulty of labeling in…
Subtype-Aware Dynamic Unsupervised Domain Adaptation
Xiaofeng Liu, Fangxu Xing, Jia You +4
Unsupervised domain adaptation (UDA) has been successfully applied to transfer knowledge from a labeled source domain to target domains without their labels. Recently introduced tr…
Deep Unsupervised Domain Adaptation: A Review of Recent Advances and Perspectives
Xiaofeng Liu, Chaehwa Yoo, Fangxu Xing +4
Deep learning has become the method of choice to tackle real-world problems in different domains, partly because of its ability to learn from data and achieve impressive performanc…
Feasibility study of clinical target volume definition for soft-tissue sarcoma using muscle fiber orientations derived from diffusion tensor imaging
Nadya Shusharina, Xiaofeng Liu, Jaume Coll-Font +5
Objective: Soft-tissue sarcoma spreads preferentially along muscle fibers. We explore the utility of deriving muscle fiber orientations from diffusion tensor MRI (DT-MRI) for defin…
ACT: Semi-supervised Domain-adaptive Medical Image Segmentation with Asymmetric Co-training
Xiaofeng Liu, Fangxu Xing, Nadya Shusharina +4
Unsupervised domain adaptation (UDA) has been vastly explored to alleviate domain shifts between source and target domains, by applying a well-performed model in an unlabeled targe…
Tagged-MRI Sequence to Audio Synthesis via Self Residual Attention Guided Heterogeneous Translator
Xiaofeng Liu, Fangxu Xing, Jerry L. Prince +4
Understanding the underlying relationship between tongue and oropharyngeal muscle deformation seen in tagged-MRI and intelligible speech plays an important role in advancing speech…
Structure-aware Unsupervised Tagged-to-Cine MRI Synthesis with Self Disentanglement
Xiaofeng Liu, Fangxu Xing, Jerry L. Prince +3
Cycle reconstruction regularized adversarial training -- e.g., CycleGAN, DiscoGAN, and DualGAN -- has been widely used for image style transfer with unpaired training data. Several…
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…
Self-semantic contour adaptation for cross modality brain tumor segmentation
Xiaofeng Liu, Fangxu Xing, Georges El Fakhri +1
Unsupervised domain adaptation (UDA) between two significantly disparate domains to learn high-level semantic alignment is a crucial yet challenging task.~To this end, in this work…