12 papers
Personalising Deformable Image Registration with Clinical Context and Deformation History for Adaptive Radiotherapy
Caiwen Jiang, Songlin Zhao, Yuzhen Ding +23
Adaptive radiotherapy must account for anatomical changes during treatment, but doing so depends on reliably mapping targets, organs at risk and dose across serial images. Existing…
Can We Defend Against AI-Generated Video Attacks on Real-World Crisis Events? A Systematic Evaluation of Detectors, Generators and Social Dissemination
Shuo Liang, Yixing Ma, Pengfei Zhou +33
Recent video generators can fabricate realistic depictions of wars, disasters, public emergencies, and other real-world crises, creating substantial risks of misinformation. Existi…
Towards a Virtual Neuroscientist: Autonomous Neuroimaging Analysis via Multi-Agent Collaboration
Keqi Han, Songlin Zhao, Yao Su +4
Transforming neuroimaging data into clinically actionable biomarkers is a knowledge-intensive and labor-intensive process. Standardized workflows such as fMRIPrep have improved rob…
Supervised Deep Multimodal Matrix Factorization for Interpretable Brain Network Analysis
Amjad Seyedi, Lifang He, Songlin Zhao +2
Multimodal brain network analysis faces a persistent trade-off between predictive accuracy and interpretability. Deep neural networks achieve high accuracy but behave as black boxe…
Homodyne Photonic Tensor Processor exceeds 1,000-TOPS
Lian Zhou, Kaiwen Xue, Yun-Jhu Lee +10
High-performance computing underpins modern artificial intelligence (AI), enabling foundation models, real-time inference and perception in autonomous systems, and data-intensive s…
MedGPT-oss: Training a General-Purpose Vision-Language Model for Biomedicine
Kai Zhang, Zhengqing Yuan, Cheng Peng +10
Biomedical multimodal assistants have the potential to unify radiology, pathology, and clinical-text reasoning, yet a critical deployment gap remains: top-performing systems are ei…
Quantization-aware Photonic Homodyne computing for Accelerated Artificial Intelligence and Scientific Simulation
Lian Zhou, Kaiwen Xue, Amirhossein Fallah +14
Modern problems in high-performance computing, ranging from training and inferencing deep learning models in computer vision and language models to simulating complex physical syst…
EfficientXpert: Efficient Domain Adaptation for Large Language Models via Propagation-Aware Pruning
Songlin Zhao, Michael Pitts, Zhuwei Qin
Deploying domain-specialized large language models on resource-constrained hardware motivates reducing both adaptation cost and the number of retained weights. LoRA lowers adaptati…
Is the medical image segmentation problem solved? A survey of current developments and future directions
Guoping Xu, Jayaram K. Udupa, Jax Luo +8
Medical image segmentation has advanced rapidly over the past two decades, largely driven by deep learning, which has enabled accurate and efficient delineation of cells, tissues,…
Segment Anything for Video: A Comprehensive Review of Video Object Segmentation and Tracking from Past to Future
Guoping Xu, Jayaram K. Udupa, Yajun Yu +4
Video Object Segmentation and Tracking (VOST) presents a complex yet critical challenge in computer vision, requiring robust integration of segmentation and tracking across tempora…
SegImgNet: Segmentation-Guided Dual-Branch Network for Retinal Disease Diagnoses
Xinwei Luo, Songlin Zhao, Yun Zong +3
Retinal image plays a crucial role in diagnosing various diseases, as retinal structures provide essential diagnostic information. However, effectively capturing structural feature…
Normative Modeling for AD Diagnosis and Biomarker Identification
Songlin Zhao, Rong Zhou, Yu Zhang +2
In this paper, we introduce a novel normative modeling approach that incorporates focal loss and adversarial autoencoders (FAAE) for Alzheimer's Disease (AD) diagnosis and biomarke…