21 citations · 57 across the 28 of their papers we have counts for
30 papers
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…
Rethink Domain Generalization in Heterogeneous Sequence MRI Segmentation
Zheyuan Zhang, Linkai Peng, Wanying Dou +6
Clinical magnetic-resonance (MR) protocols generate many T1 and T2 sequences whose appearance differs more than the acquisition sites that produce them. Existing domain-generalizat…
Cyst-X: A Multicenter MRI Benchmark for Pancreatic Cyst Risk Stratification and Cross-Institutional AI
Hongyi Pan, Gorkem Durak, Elif Keles +29
Intraductal papillary mucinous neoplasms (IPMNs) are pancreatic cancer precursors, and guideline-based risk stratification both over-treats indolent lesions and misses progression.…
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…
TAGS: 3D Tumor-Adaptive Guidance for SAM
Sirui Li, Linkai Peng, Zheyuan Zhang +2
Foundation models (FMs) such as CLIP and SAM have recently shown great promise in image segmentation tasks, yet their adaptation to 3D medical imaging-particularly for pathology de…
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…
IPMN Risk Assessment under Federated Learning Paradigm
Hongyi Pan, Ziliang Hong, Gorkem Durak +17
Accurate classification of Intraductal Papillary Mucinous Neoplasms (IPMN) is essential for identifying high-risk cases that require timely intervention. In this study, we develop…
Adaptive Aggregation Weights for Federated Segmentation of Pancreas MRI
Hongyi Pan, Gorkem Durak, Zheyuan Zhang +16
Federated learning (FL) enables collaborative model training across institutions without sharing sensitive data, making it an attractive solution for medical imaging tasks. However…
Optimizing Synthetic Data for Enhanced Pancreatic Tumor Segmentation
Linkai Peng, Zheyuan Zhang, Gorkem Durak +4
Pancreatic cancer remains one of the leading causes of cancer-related mortality worldwide. Precise segmentation of pancreatic tumors from medical images is a bottleneck for effecti…
Ethical Framework for Responsible Foundational Models in Medical Imaging
Debesh Jha, Gorkem Durak, Abhijit Das +33
The emergence of foundational models represents a paradigm shift in medical imaging, offering extraordinary capabilities in disease detection, diagnosis, and treatment planning. Th…
Segmentation Quality and Volumetric Accuracy in Medical Imaging
Zheyuan Zhang, Ulas Bagci
Current medical image segmentation relies on the region-based (Dice, F1-score) and boundary-based (Hausdorff distance, surface distance) metrics as the de-facto standard. While the…
MDNet: Multi-Decoder Network for Abdominal CT Organs Segmentation
Debesh Jha, Nikhil Kumar Tomar, Koushik Biswas +11
Accurate segmentation of organs from abdominal CT scans is essential for clinical applications such as diagnosis, treatment planning, and patient monitoring. To handle challenges o…
PAM-UNet: Shifting Attention on Region of Interest in Medical Images
Abhijit Das, Debesh Jha, Vandan Gorade +7
Computer-aided segmentation methods can assist medical personnel in improving diagnostic outcomes. While recent advancements like UNet and its variants have shown promise, they fac…
Large-Scale Multi-Center CT and MRI Segmentation of Pancreas with Deep Learning
Zheyuan Zhang, Elif Keles, Gorkem Durak +35
Automated volumetric segmentation of the pancreas on cross-sectional imaging is needed for diagnosis and follow-up of pancreatic diseases. While CT-based pancreatic segmentation is…
Detection of Peri-Pancreatic Edema using Deep Learning and Radiomics Techniques
Ziliang Hong, Debesh Jha, Koushik Biswas +9
Identifying peri-pancreatic edema is a pivotal indicator for identifying disease progression and prognosis, emphasizing the critical need for accurate detection and assessment in p…
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…
Radiomics Boosts Deep Learning Model for IPMN Classification
Lanhong Yao, Zheyuan Zhang, Ugur Demir +14
Intraductal Papillary Mucinous Neoplasm (IPMN) cysts are pre-malignant pancreas lesions, and they can progress into pancreatic cancer. Therefore, detecting and stratifying their ri…
Ensemble Learning with Residual Transformer for Brain Tumor Segmentation
Lanhong Yao, Zheyuan Zhang, Ulas Bagci
Brain tumor segmentation is an active research area due to the difficulty in delineating highly complex shaped and textured tumors as well as the failure of the commonly used U-Net…
Validating polyp and instrument segmentation methods in colonoscopy through Medico 2020 and MedAI 2021 Challenges
Debesh Jha, Vanshali Sharma, Debapriya Banik +30
Automatic analysis of colonoscopy images has been an active field of research motivated by the importance of early detection of precancerous polyps. However, detecting polyps durin…
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…