ArticleQuantitative imaging in medicine and surgery2014
Enhancement of the low resolution image quality using randomly sampled data for multi-slice MR imaging.
Article in Quantitative imaging in medicine and surgery, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Evaluation of magnetic resonance image segmentation in brain low-grade gliomas using support vector machine and convolutional neural network.Quantitative imaging in medicine and surgery · 2021Article
- Radial Undersampling-Based Interpolation Scheme for Multislice CSMRI Reconstruction Techniques.BioMed research international · 2021Article
- Chemical Exchange Saturation Transfer (CEST) MR Technique for Liver Imaging at 3.0 Tesla: an Evaluation of Different Offset Number and an After-Meal and Over-Night-Fast Comparison.Molecular imaging and biology · 2016Article
- Improved image reconstruction of low-resolution multichannel phase contrast angiography.Journal of medical imaging (Bellingham, Wash.) · 2016Article
- Magnetic resonance imaging for lung cancer screen.Journal of thoracic disease · 2014Review
- Parallel and sparse MR imaging: methods and instruments-Part 2.Quantitative imaging in medicine and surgery · 2014Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Low resolution images are often acquired in in vivo MR applications involving in large field-of-view (FOV) and high speed imaging, such as, whole-body MRI screening and functional MRI applications. In this work, we investigate a multi-slice imaging strategy for acquiring low resolution images by using compressed sensing (CS) MRI to enhance the image quality without increasing the acquisition time. In this strategy, low resolution images of all the slices are acquired using multiple-slice imaging sequence. In addition, extra randomly sampled data in one center slice are acquired by using the CS strategy. These additional randomly sampled data are multiplied by the weighting functions generated from low resolution full k-space images of the two slices, and then interpolated into the k-space of other slices. In vivo MR images of human brain were employed to investigate the feasibility and the performance of the proposed method. Quantitative comparison between the conventional low resolution images and those from the proposed method was also performed to demonstrate the advantage of the method.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.