Search Results for author: Haimiao Zhang

Found 5 papers, 1 papers with code

InDuDoNet: An Interpretable Dual Domain Network for CT Metal Artifact Reduction

1 code implementation11 Sep 2021 Hong Wang, Yuexiang Li, Haimiao Zhang, Jiawei Chen, Kai Ma, Deyu Meng, Yefeng Zheng

For the task of metal artifact reduction (MAR), although deep learning (DL)-based methods have achieved promising performances, most of them suffer from two problems: 1) the CT imaging geometry constraint is not fully embedded into the network during training, leaving room for further performance improvement; 2) the model interpretability is lack of sufficient consideration.

Metal Artifact Reduction

Improving Generalizability in Limited-Angle CT Reconstruction with Sinogram Extrapolation

no code implementations9 Mar 2021 Ce Wang, Haimiao Zhang, Qian Li, Kun Shang, Yuanyuan Lyu, Bin Dong, S. Kevin Zhou

More importantly, we show that using such a sinogram extrapolation module significantly improves the generalization capability of the model on unseen datasets (e. g., COVID-19 and LIDC datasets) when compared to existing approaches.

Computed Tomography (CT)

A Review on Deep Learning in Medical Image Reconstruction

no code implementations23 Jun 2019 Haimiao Zhang, Bin Dong

More recently, as more data and computation resources are made available, deep learning based models (or deep models) pushed the data-driven modeling to the extreme where the models are mostly based on learning with minimal human designs.

Image Reconstruction Image Restoration

JSR-Net: A Deep Network for Joint Spatial-Radon Domain CT Reconstruction from incomplete data

no code implementations3 Dec 2018 Haimiao Zhang, Bin Dong, Baodong Liu

CT image reconstruction from incomplete data, such as sparse views and limited angle reconstruction, is an important and challenging problem in medical imaging.

Image Reconstruction

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