14 citations · 19 across the 10 of their papers we have counts for
10 papers
Detector-in-the-Loop Tracking: Active Memory Rectification for Stable Glottic Opening Localization
Huayu Wang, Bahaa Alattar, Cheng-Yen Yang +5
Temporal stability in glottic opening localization remains challenging due to the complementary weaknesses of single-frame detectors and foundation-model trackers: the former lacks…
Towards Globally Predictable k-Space Interpolation: A White-box Transformer Approach
Chen Luo, Qiyu Jin, Taofeng Xie +7
Interpolating missing data in k-space is essential for accelerating imaging. However, existing methods, including convolutional neural network-based deep learning, primarily exploi…
TEMPURA: Temporal Event Masked Prediction and Understanding for Reasoning in Action
Jen-Hao Cheng, Vivian Wang, Huayu Wang +11
Understanding causal event relationships and achieving fine-grained temporal grounding in videos remain challenging for vision-language models (VLMs). We propose TEMPURA (Temporal…
CrossFusion: A Multi-Scale Cross-Attention Convolutional Fusion Model for Cancer Survival Prediction
Rustin Soraki, Huayu Wang, Sitong Liu +2
Cancer survival prediction from whole slide images (WSIs) is a challenging task in computational pathology due to the large size, irregular shape, and high granularity of the WSIs.…
Joint PET-MRI Reconstruction with Diffusion Stochastic Differential Model
Taofeng Xie, Zhuoxu Cui, Congcong Liu +9
PET suffers from a low signal-to-noise ratio. Meanwhile, the k-space data acquisition process in MRI is time-consuming by PET-MRI systems. We aim to accelerate MRI and improve PET…
The TopCoW Challenge -- Topology-Aware Circle of Willis Segmentation for CT and MR Angiography
Kaiyuan Yang, Fabio Musio, Yihui Ma +112
The Circle of Willis (CoW) is an important network of arteries connecting major circulations of the brain. Its vascular architecture is believed to influence the risk, severity, an…
Joint Diffusion: Mutual Consistency-Driven Diffusion Model for PET-MRI Co-Reconstruction
Taofeng Xie, Zhuo-Xu Cui, Chen Luo +10
Positron Emission Tomography and Magnetic Resonance Imaging (PET-MRI) systems can obtain functional and anatomical scans. PET suffers from a low signal-to-noise ratio. Meanwhile, t…
Matrix Completion-Informed Deep Unfolded Equilibrium Models for Self-Supervised k-Space Interpolation in MRI
Chen Luo, Huayu Wang, Taofeng Xie +4
Recently, regularization model-driven deep learning (DL) has gained significant attention due to its ability to leverage the potent representational capabilities of DL while retain…
Convex Latent-Optimized Adversarial Regularizers for Imaging Inverse Problems
Huayu Wang, Chen Luo, Taofeng Xie +4
Recently, data-driven techniques have demonstrated remarkable effectiveness in addressing challenges related to MR imaging inverse problems. However, these methods still exhibit ce…
A Survey on Label-efficient Deep Image Segmentation: Bridging the Gap between Weak Supervision and Dense Prediction
Wei Shen, Zelin Peng, Xuehui Wang +6
The rapid development of deep learning has made a great progress in image segmentation, one of the fundamental tasks of computer vision. However, the current segmentation algorithm…