High quality segmentation for ultra high-resolution images
To segment 4K or 6K ultra high-resolution images needs extra computation consideration in
image segmentation. Common strategies, such as down-sampling, patch cropping, and …
image segmentation. Common strategies, such as down-sampling, patch cropping, and …
Learning to super-resolve dynamic scenes for neuromorphic spike camera
Spike camera is a kind of neuromorphic sensor that uses a novel``integrate-and-
fire''mechanism to generate a continuous spike stream to record the dynamic light intensity …
fire''mechanism to generate a continuous spike stream to record the dynamic light intensity …
Fine‐grained crack segmentation for high‐resolution images via a multiscale cascaded network
High‐resolution (HR) crack images offer more detailed information for assessing structural
conditions compared to low‐resolution (LR) images. This wealth of detail proves …
conditions compared to low‐resolution (LR) images. This wealth of detail proves …
Self-supervised coordinate projection network for sparse-view computed tomography
Sparse-view Computed Tomography (SVCT) has great potential for decreasing patient
radiation exposure dose during scanning. In this work, we propose a Self-supervised …
radiation exposure dose during scanning. In this work, we propose a Self-supervised …
Review of sparse-view or limited-angle CT reconstruction based on deep learning
J Di, J Lin, L Zhong, K Qian, Y Qin - Laser & Optoelectronics …, 2023 - researching.cn
Computed tomography (CT) technology is widely used in clinical medical diagnosis thanks
to the excellent visualization of the CT imaging technology for the internal cross-sectional …
to the excellent visualization of the CT imaging technology for the internal cross-sectional …
Global transport for fluid reconstruction with learned self-supervision
E Franz, B Solenthaler… - Proceedings of the IEEE …, 2021 - openaccess.thecvf.com
We propose a novel method to reconstruct volumetric flows from sparse views via a global
transport formulation. Instead of obtaining the space-time function of the observations, we …
transport formulation. Instead of obtaining the space-time function of the observations, we …
Tomofluid: Reconstructing dynamic fluid from sparse view videos
Visible light tomography is a promising and increasingly popular technique for fluid imaging.
However, the use of a sparse number of viewpoints in the capturing setups makes the …
However, the use of a sparse number of viewpoints in the capturing setups makes the …
Learning projection views for sparse-view ct reconstruction
Sparse-View CT (SVCT), which provides low-dose and high-speed CT imaging, plays an
important role in the medical imaging area. As the decrease of projection views, the …
important role in the medical imaging area. As the decrease of projection views, the …
Improving the quality of sparse-view cone-beam computed tomography via reconstruction-friendly interpolation network
Y Wang, L Chao, W Shan, H Zhang… - Proceedings of the …, 2022 - openaccess.thecvf.com
Reconstructing cone-beam computed tomography (CBCT) typically utilizes a Feldkamp-
Davis-Kress (FDK) algorithm to'translate'hundreds of 2D X-ray projections on different …
Davis-Kress (FDK) algorithm to'translate'hundreds of 2D X-ray projections on different …
Unsupervised reused convolutional network for metal artifact reduction
B Zhao, J Li, Q Ren, Y Zhong - … November 18–22, 2020, Proceedings, Part …, 2020 - Springer
Nowadays computed tomography (CT) is widely used for medical diagnosis and treatment.
However, CT images are often corrupted by undesirable artifacts when metallic implants are …
However, CT images are often corrupted by undesirable artifacts when metallic implants are …