collaborators

8 papers

cs.CV2025

Cyclic Vision-Language Manipulator: Towards Reliable and Fine-Grained Image Interpretation for Automated Report Generation

Yingying Fang, Zihao Jin, Shaojie Guo +7

Despite significant advancements in automated report generation, the opaqueness of text interpretability continues to cast doubt on the reliability of the content produced. This pa…

eess.IV2024

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…

eess.IV2024

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…

eess.IV2024

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…

cs.CV2024

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…

eess.IV2024

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…