4 citations · 6 across the 9 of their papers we have counts for
9 papers
BrainIAC: Interactive 3D Brain Lesion Segmentation across Heterogeneous MRI Modalities with Online Adaptation
Wentian Xu, Anthony P Addison, Ziyun Liang +3
Brain lesion segmentation is a fundamental task in medical image analysis, playing a critical role in diagnosis, treatment planning, and longitudinal disease monitoring. Yet existi…
Motion-Conditioned Multi-View Fusion for Myocardial Infarction Localization from Echocardiography
Guang Yang, Wentian Xu, Siyu Wang +3
Myocardial infarction (MI) remains a leading cause of mortality worldwide. Echocardiography (Echo) is a widely available modality for MI assessment, where regional wall motion abno…
Modality-Agnostic Input Channels Enable Segmentation of Brain lesions in Multimodal MRI with Sequences Unavailable During Training
Anthony P. Addison, Felix Wagner, Wentian Xu +2
Segmentation models are important tools for the detection and analysis of lesions in brain MRI. Depending on the type of brain pathology that is imaged, MRI scanners can acquire mu…
Specialised or Generic? Tokenization Choices for Radiology Language Models
Hermione Warr, Wentian Xu, Harry Anthony +3
The vocabulary used by language models (LM) - defined by the tokenizer - plays a key role in text generation quality. However, its impact remains under-explored in radiology. In th…
IterMask3D: Unsupervised Anomaly Detection and Segmentation with Test-Time Iterative Mask Refinement in 3D Brain MR
Ziyun Liang, Xiaoqing Guo, Wentian Xu +5
Unsupervised anomaly detection and segmentation methods train a model to learn the training distribution as `normal'. In the testing phase, they identify patterns that deviate from…
You Point, I Learn: Online Adaptation of Interactive Segmentation Models for Handling Distribution Shifts in Medical Imaging
Wentian Xu, Ziyun Liang, Harry Anthony +4
Interactive segmentation uses real-time user inputs, such as mouse clicks, to iteratively refine model predictions. Although not originally designed to address distribution shifts,…
Feasibility of Federated Learning from Client Databases with Different Brain Diseases and MRI Modalities
Felix Wagner, Wentian Xu, Pramit Saha +7
Segmentation models for brain lesions in MRI are typically developed for a specific disease and trained on data with a predefined set of MRI modalities. Such models cannot segment…
Feasibility and benefits of joint learning from MRI databases with different brain diseases and modalities for segmentation
Wentian Xu, Matthew Moffat, Thalia Seale +8
Models for segmentation of brain lesions in multi-modal MRI are commonly trained for a specific pathology using a single database with a predefined set of MRI modalities, determine…
Revisiting Implicit Neural Representations in Low-Level Vision
Wentian Xu, Jianbo Jiao
Implicit Neural Representation (INR) has been emerging in computer vision in recent years. It has been shown to be effective in parameterising continuous signals such as dense 3D m…