activity
20232025
most citedReduced Deep Convolutional Activation Features (R-DeCAF) in Histopathology Images to Improve the Classification Performance for Breast Cancer Diagnosis

29 citations · 49 across the 7 of their papers we have counts for

collaborators

7 papers

eess.IV2025

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…

cs.CV2025

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…

eess.IV2025

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…

eess.IV2024

-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…

eess.IV2024★ 19 cited

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…

eess.IV2023★ 1 cited

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,…

cs.CV2023★ 29 cited

Reduced Deep Convolutional Activation Features (R-DeCAF) in Histopathology Images to Improve the Classification Performance for Breast Cancer Diagnosis

Bahareh Morovati, Reza Lashgari, Mojtaba Hajihasani +1

Breast cancer is the second most common cancer among women worldwide. Diagnosis of breast cancer by the pathologists is a time-consuming procedure and subjective. Computer aided di…