activity
20242026
most citedMixture of Multicenter Experts in Multimodal AI for Debiased Radiotherapy Target Delineation

2 citations · 5 across the 20 of their papers we have counts for

collaborators
Showing 2026Show all

6 papers · 1 filter

eess.IV2026

Coronary Mask Guided Registration for Continuous Time 4D Cardiac CT Dataset Construction

Yuang Wang, Shuo Wang, Changyu Chen +12

Objective: Clinical cardiac CT multiphase reconstructions generally provide acceptable image quality in end-diastole (ED) or end-systole (ES) phases, but in other phases may exhibi…

cs.CV2026

Hallucination-Aware Diffusion Sampling for Inverse Problems via Robust Prior Updates

Pengfei Jin, Yiqi Tian, Kailong Fan +2

Diffusion-based inverse problem solvers can produce realistic reconstructions, but realism alone does not ensure that the recovered details are supported by the measurement. We stu…

cs.LG2026

Measurement Geometry and Design for Trustworthy Generative Inverse Problems

Pengfei Jin, Na Li, Quanzheng Li

Generative models are increasingly used as priors for inverse problems, but their ability to produce realistic images creates a basic trust problem: a plausible reconstruction may…

cs.CV2026

LiFT: Lifted Inter-slice Feature Trajectories for 3D Image Generation from 2D Generators

Xinhe Zhang, Yuyang Zhang, Pengfei Jin +3

High-resolution 3D medical image generation remains challenging because fully volumetric models are computationally expensive, while efficient 2D slice generators often fail to pre…

cs.CV2026

DuetMoE: Coupling Inter- and Intra-Subgroup Robustness for Fair Medical Image Analysis

Yiqi Tian, Sangjoon Park, Jinwoong Park +4

As medical AI expands across diverse healthcare settings worldwide, equitable performance across patient populations is becoming essential to trustworthy clinical use. Fairness in…

cs.CV2026

Local Intrinsic Dimension Unveils Hallucinations in Diffusion Models

Bartlomiej Sobieski, Matthew Tivnan, Dawid Płudowski +4

Diffusion models are prone to generating structural hallucinations - samples that match the statistical properties of the training data yet defy underlying structural rules, result…