16 citations · 20 across the 6 of their papers we have counts for
8 papers
PathoArgus: Advancing Evidence-Grounded Long-Context Visual Reasoning across Gigapixel Whole-Slide and Multi-Slide Case Contexts
Bowen Liu, Qixiang Zhang, Xiaomeng Li
Whole-slide pathology reasoning requires models to integrate gigapixel-scale visual evidence across complete case-linked slides, yet current question-answering benchmarks primarily…
A Cognitive Process-Inspired Architecture for Subject-Agnostic Brain Visual Decoding
Jingyu Lu, Haonan Wang, Qixiang Zhang +1
Subject-agnostic brain decoding, which aims to reconstruct continuous visual experiences from fMRI without subject-specific training, holds great potential for clinical application…
ZEBRA: Towards Zero-Shot Cross-Subject Generalization for Universal Brain Visual Decoding
Haonan Wang, Jingyu Lu, Hongrui Li +1
Recent advances in neural decoding have enabled the reconstruction of visual experiences from brain activity, positioning fMRI-to-image reconstruction as a promising bridge between…
Synergistic Vision-Language Reinforcement Enables Scalable On-Demand Analysis across Diverse Clinical Tasks
Haonan Wang, Jiaji Mao, Lehan Wang +11
Accurate segmentation of tumors and organs-at-risk is essential for oncology but remains time-consuming and expertise-intensive. Existing AI systems often require manual spatial pr…
Neurons: Emulating the Human Visual Cortex Improves Fidelity and Interpretability in fMRI-to-Video Reconstruction
Haonan Wang, Qixiang Zhang, Lehan Wang +2
Decoding visual stimuli from neural activity is essential for understanding the human brain. While fMRI methods have successfully reconstructed static images, fMRI-to-video reconst…
S&D Messenger: Exchanging Semantic and Domain Knowledge for Generic Semi-Supervised Medical Image Segmentation
Qixiang Zhang, Haonan Wang, Xiaomeng Li
Semi-supervised medical image segmentation (SSMIS) has emerged as a promising solution to tackle the challenges of time-consuming manual labeling in the medical field. However, in…
AllSpark: Reborn Labeled Features from Unlabeled in Transformer for Semi-Supervised Semantic Segmentation
Haonan Wang, Qixiang Zhang, Yi Li +1
Semi-supervised semantic segmentation (SSSS) has been proposed to alleviate the burden of time-consuming pixel-level manual labeling, which leverages limited labeled data along wit…
Towards Generic Semi-Supervised Framework for Volumetric Medical Image Segmentation
Haonan Wang, Xiaomeng Li
Volume-wise labeling in 3D medical images is a time-consuming task that requires expertise. As a result, there is growing interest in using semi-supervised learning (SSL) technique…