26 citations · 26 across the 6 of their papers we have counts for
6 papers
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…
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…
DiffExplainer: Unveiling Black Box Models Via Counterfactual Generation
Yingying Fang, Shuang Wu, Zihao Jin +4
In the field of medical imaging, particularly in tasks related to early disease detection and prognosis, understanding the reasoning behind AI model predictions is imperative for a…
Hunting imaging biomarkers in pulmonary fibrosis: Benchmarks of the AIIB23 challenge
Yang Nan, Xiaodan Xing, Shiyi Wang +38
Airway-related quantitative imaging biomarkers are crucial for examination, diagnosis, and prognosis in pulmonary diseases. However, the manual delineation of airway trees remains…
Post-COVID Highlights: Challenges and Solutions of AI Techniques for Swift Identification of COVID-19
Yingying Fang, Xiaodan Xing, Shiyi Wang +2
Since the onset of the COVID-19 pandemic in 2019, there has been a concerted effort to develop cost-effective, non-invasive, and rapid AI-based tools. These tools were intended to…