19 citations · 22 across the 10 of their papers we have counts for
10 papers
PoCGM: Poisson-Conditioned Generative Model for Sparse-View CT Reconstruction
Changsheng Fang, Yongtong Liu, Bahareh Morovati +3
In computed tomography (CT), reducing the number of projection views is an effective strategy to lower radiation exposure and/or improve temporal resolution. However, this often re…
Cross-Distribution Diffusion Priors-Driven Iterative Reconstruction for Sparse-View CT
Haodong Li, Shuo Han, Haiyang Mao +5
Sparse-View CT (SVCT) reconstruction enhances temporal resolution and reduces radiation dose, yet its clinical use is hindered by artifacts due to view reduction and domain shifts…
Clinical Metadata Guided Limited-Angle CT Image Reconstruction
Yu Shi, Shuyi Fan, Changsheng Fang +6
Limited-angle computed tomography (LACT) offers improved temporal resolution and reduced radiation dose for cardiac imaging, but suffers from severe artifacts due to truncated proj…
Towards Human-AI Collaboration System for the Detection of Invasive Ductal Carcinoma in Histopathology Images
Shuo Han, Ahmed Karam Eldaly, Solomon Sunday Oyelere
Invasive ductal carcinoma (IDC) is the most prevalent form of breast cancer, and early, accurate diagnosis is critical to improving patient survival rates by guiding treatment deci…
ResPF: Residual Poisson Flow for Efficient and Physically Consistent Sparse-View CT Reconstruction
Changsheng Fang, Yongtong Liu, Bahareh Morovati +5
Sparse-view computed tomography (CT) is a practical solution to reduce radiation dose, but the resulting ill-posed inverse problem poses significant challenges for accurate image r…
-NeRF: Leveraging Attenuation Priors in Neural Radiance Field for 3D Computed Tomography Reconstruction
Li Zhou, Changsheng Fang, Bahareh Morovati +4
This paper introduces -NeRF, a self-supervised approach that sets a new standard in novel view synthesis (NVS) and computed tomography (CT) reconstruction by modeling a continuo…
Pretrained Event Classification Model for High Energy Physics Analysis
Joshua Ho, Benjamin Ryan Roberts, Shuo Han +1
We introduce a foundation model for event classification in high-energy physics, built on a Graph Neural Network architecture and trained on 120 million simulated proton-proton col…
Soft-Label Integration for Robust Toxicity Classification
Zelei Cheng, Xian Wu, Jiahao Yu +3
Toxicity classification in textual content remains a significant problem. Data with labels from a single annotator fall short of capturing the diversity of human perspectives. Ther…
Physics-informed Score-based Diffusion Model for Limited-angle Reconstruction of Cardiac Computed Tomography
Shuo Han, Yongshun Xu, Dayang Wang +5
Cardiac computed tomography (CT) has emerged as a major imaging modality for the diagnosis and monitoring of cardiovascular diseases. High temporal resolution is essential to ensur…
LoMAE: Low-level Vision Masked Autoencoders for Low-dose CT Denoising
Dayang Wang, Yongshun Xu, Shuo Han +4
Low-dose computed tomography (LDCT) offers reduced X-ray radiation exposure but at the cost of compromised image quality, characterized by increased noise and artifacts. Recently,…