21 citations · 57 across the 28 of their papers we have counts for
12 papers · 1 filter
SonoWorld: Towards Interactive Pose-Controllable Ultrasound World Models
Zefan Yang, Zheyuan Zhang, Boris Maihe +7
Robotic ultrasound can standardize image acquisition and reduce operator workload and variability, but policy learning remains limited by the lack of realistic, controllable simula…
CrossPan: A Comprehensive Benchmark for Cross-Sequence Pancreas MRI Segmentation and Generalization
Linkai Peng, Cuiling Sun, Zheyuan Zhang +10
Automatic pancreas segmentation is fundamental to abdominal MRI analysis, yet deep learning models trained on one MRI sequence often fail catastrophically when applied to another-a…
Pancreas Part Segmentation under Federated Learning Paradigm
Ziliang Hong, Halil Ertugrul Aktas, Andrea Mia Bejar +15
We present the first federated learning (FL) approach for pancreas part(head, body and tail) segmentation in MRI, addressing a critical clinical challenge as a significant innovati…
RAU: Reference-based Anatomical Understanding with Vision Language Models
Yiwei Li, Yikang Liu, Jiaqi Guo +7
Anatomical understanding, which is the ability to identify, localize, or segment anatomical structures, is critical in medical image analysis; however, its progress is constrained…
Pediatric Pancreas Segmentation from MRI Scans with Deep Learning
Elif Keles, Merve Yazol, Gorkem Durak +11
Objective: Our study aimed to evaluate and validate PanSegNet, a deep learning (DL) algorithm for pediatric pancreas segmentation on MRI in children with acute pancreatitis (AP), c…
VideoAds for Fast-Paced Video Understanding
Zheyuan Zhang, Monica Dou, Linkai Peng +3
Advertisement videos serve as a rich and valuable source of purpose-driven information, encompassing high-quality visual, textual, and contextual cues designed to engage viewers. T…
Explainable Transformer Prototypes for Medical Diagnoses
Ugur Demir, Debesh Jha, Zheyuan Zhang +4
Deployments of artificial intelligence in medical diagnostics mandate not just accuracy and efficacy but also trust, emphasizing the need for explainability in machine decisions. T…
DiffBoost: Enhancing Medical Image Segmentation via Text-Guided Diffusion Model
Zheyuan Zhang, Lanhong Yao, Bin Wang +5
Large-scale, big-variant, high-quality data are crucial for developing robust and successful deep-learning models for medical applications since they potentially enable better gene…
GazeGNN: A Gaze-Guided Graph Neural Network for Chest X-ray Classification
Bin Wang, Hongyi Pan, Armstrong Aboah +7
Eye tracking research is important in computer vision because it can help us understand how humans interact with the visual world. Specifically for high-risk applications, such as…
GazeSAM: What You See is What You Segment
Bin Wang, Armstrong Aboah, Zheyuan Zhang +1
This study investigates the potential of eye-tracking technology and the Segment Anything Model (SAM) to design a collaborative human-computer interaction system that automates med…
Domain Generalization with Correlated Style Uncertainty
Zheyuan Zhang, Bin Wang, Debesh Jha +2
Domain generalization (DG) approaches intend to extract domain invariant features that can lead to a more robust deep learning model. In this regard, style augmentation is a strong…
Dynamic Linear Transformer for 3D Biomedical Image Segmentation
Zheyuan Zhang, Ulas Bagci
Transformer-based neural networks have surpassed promising performance on many biomedical image segmentation tasks due to a better global information modeling from the self-attenti…