8 papers · 1 filter
Enhancing Weakly Supervised Semantic Segmentation for Fibrosis via Controllable Image Generation
Zhiling Yue, Yingying Fang, Liutao Yang +3
Fibrotic Lung Disease (FLD) is a severe condition marked by lung stiffening and scarring, leading to respiratory decline. High-resolution computed tomography (HRCT) is critical for…
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…
Diff3Dformer: Leveraging Slice Sequence Diffusion for Enhanced 3D CT Classification with Transformer Networks
Zihao Jin, Yingying Fang, Jiahao Huang +3
The manifestation of symptoms associated with lung diseases can vary in different depths for individual patients, highlighting the significance of 3D information in CT scans for me…
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…
Make it more specific: A novel uncertainty based airway segmentation application on 3D U-Net and its variants
Shiyi Wang, Yang Nan, Felder Federico N +3
Each medical segmentation task should be considered with a specific AI algorithm based on its scenario so that the most accurate prediction model can be obtained. The most popular…
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…