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14 papers · 2 filters
Deep learning for fast MR imaging: a review for learning reconstruction from incomplete k-space data
Shanshan Wang, Taohui Xiao, Qiegen Liu +1
Magnetic resonance imaging is a powerful imaging modality that can provide versatile information but it has a bottleneck problem "slow imaging speed". Reducing the scanned measurem…
Annotation-efficient deep learning for automatic medical image segmentation
Shanshan Wang, Cheng Li, Rongpin Wang +12
Automatic medical image segmentation plays a critical role in scientific research and medical care. Existing high-performance deep learning methods typically rely on large training…
Image Quality Assessment for Perceptual Image Restoration: A New Dataset, Benchmark and Metric
Jinjin Gu, Haoming Cai, Haoyu Chen +3
Image quality assessment (IQA) is the key factor for the fast development of image restoration (IR) algorithms. The most recent perceptual IR algorithms based on generative adversa…
Dynamic radiomics: a new methodology to extract quantitative time-related features from tomographic images
Fengying Che, Ruichuan Shi, Jian Wu +6
The feature extraction methods of radiomics are mainly based on static tomographic images at a certain moment, while the occurrence and development of disease is a dynamic process…
Efficient Image Super-Resolution Using Pixel Attention
Hengyuan Zhao, Xiangtao Kong, Jingwen He +2
This work aims at designing a lightweight convolutional neural network for image super resolution (SR). With simplicity bare in mind, we construct a pretty concise and effective ne…
Deep Low-rank plus Sparse Network for Dynamic MR Imaging
Wenqi Huang, Ziwen Ke, Zhuo-Xu Cui +6
In dynamic magnetic resonance (MR) imaging, low-rank plus sparse (L+S) decomposition, or robust principal component analysis (PCA), has achieved stunning performance. However, the…