26 citations · 43 across the 23 of their papers we have counts for
14 papers · 1 filter
Anatomy-Guided Radiology Report Generation with Pathology-Aware Regional Prompts
Yijian Gao, Dominic Marshall, Xiaodan Xing +4
Radiology reporting generative AI holds significant potential to alleviate clinical workloads and streamline medical care. However, achieving high clinical accuracy is challenging,…
Deep Generative Models Unveil Patterns in Medical Images Through Vision-Language Conditioning
Xiaodan Xing, Junzhi Ning, Yang Nan +1
Deep generative models have significantly advanced medical imaging analysis by enhancing dataset size and quality. Beyond mere data augmentation, our research in this paper highlig…
Preserving Cardiac Integrity: A Topology-Infused Approach to Whole Heart Segmentation
Chenyu Zhang, Wenxue Guan, Xiaodan Xing +1
Whole heart segmentation (WHS) supports cardiovascular disease (CVD) diagnosis, disease monitoring, treatment planning, and prognosis. Deep learning has become the most widely used…
MONICA: Benchmarking on Long-tailed Medical Image Classification
Lie Ju, Siyuan Yan, Yukun Zhou +4
Long-tailed learning is considered to be an extremely challenging problem in data imbalance learning. It aims to train well-generalized models from a large number of images that fo…
Coupling AI and Citizen Science in Creation of Enhanced Training Dataset for Medical Image Segmentation
Amir Syahmi, Xiangrong Lu, Yinxuan Li +7
Recent advancements in medical imaging and artificial intelligence (AI) have greatly enhanced diagnostic capabilities, but the development of effective deep learning (DL) models is…
CIResDiff: A Clinically-Informed Residual Diffusion Model for Predicting Idiopathic Pulmonary Fibrosis Progression
Caiwen Jiang, Xiaodan Xing, Zaixin Ou +4
The progression of Idiopathic Pulmonary Fibrosis (IPF) significantly correlates with higher patient mortality rates. Early detection of IPF progression is critical for initiating t…
Beyond the Hype: A dispassionate look at vision-language models in medical scenario
Yang Nan, Huichi Zhou, Xiaodan Xing +1
Recent advancements in Large Vision-Language Models (LVLMs) have demonstrated remarkable capabilities across diverse tasks, garnering significant attention in AI communities. Howev…
A dual-task mutual learning framework for predicting post-thrombectomy cerebral hemorrhage
Caiwen Jiang, Tianyu Wang, Xiaodan Xing +4
Ischemic stroke is a severe condition caused by the blockage of brain blood vessels, and can lead to the death of brain tissue due to oxygen deprivation. Thrombectomy has become a…
Artificial Immunofluorescence in a Flash: Rapid Synthetic Imaging from Brightfield Through Residual Diffusion
Xiaodan Xing, Chunling Tang, Siofra Murdoch +10
Immunofluorescent (IF) imaging is crucial for visualizing biomarker expressions, cell morphology and assessing the effects of drug treatments on sub-cellular components. IF imaging…
Probing Perfection: The Relentless Art of Meddling for Pulmonary Airway Segmentation from HRCT via a Human-AI Collaboration Based Active Learning Method
Shiyi Wang, Yang Nan, Sheng Zhang +6
In pulmonary tracheal segmentation, the scarcity of annotated data is a prevalent issue in medical segmentation. Additionally, Deep Learning (DL) methods face challenges: the opaci…
Fuzzy Attention-based Border Rendering Network for Lung Organ Segmentation
Sheng Zhang, Yang Nan, Yingying Fang +4
Automatic lung organ segmentation on CT images is crucial for lung disease diagnosis. However, the unlimited voxel values and class imbalance of lung organs can lead to false-negat…
Decoding Decision Reasoning: A Counterfactual-Powered Model for Knowledge Discovery
Yingying Fang, Zihao Jin, Xiaodan Xing +2
In medical imaging, particularly in early disease detection and prognosis tasks, discerning the rationale behind an AI model's predictions is crucial for evaluating the reliability…
When AI Eats Itself: On the Caveats of AI Autophagy
Xiaodan Xing, Fadong Shi, Jiahao Huang +8
Generative Artificial Intelligence (AI) technologies and large models are producing realistic outputs across various domains, such as images, text, speech, and music. Creating thes…
Assessing the Efficacy of Invisible Watermarks in AI-Generated Medical Images
Xiaodan Xing, Huiyu Zhou, Yingying Fang +1
AI-generated medical images are gaining growing popularity due to their potential to address the data scarcity challenge in the real world. However, the issue of accurate identific…