Accelerated cardiac cine MRI using spatiotemporal correlation-based hybrid plug-and-play priors (SEABUS)

计算机科学 人工智能 算法 方向(向量空间) 计算机视觉 模式识别(心理学) 数学 几何学
作者
Qingyong Zhu,Bei Liu,Zhuo‐Xu Cui,Jing Cheng,Chentao Cao,Yuanyuan Liu,Dong Liang,Yanjie Zhu
出处
期刊:Physics in Medicine and Biology [IOP Publishing]
卷期号:67 (21): 215008-215008 被引量:1
标识
DOI:10.1088/1361-6560/ac9662
摘要

Objective. The plug-and-play prior (P3) can be flexibly coupled with multiple iterative optimizations, which has been successfully applied to the inverse problems of medical imaging. In this work, for accelerated cardiac cine magnetic resonance imaging (CC-MRI), the Spatiotemporal corrElAtion-based hyBrid plUg-and-play priorS (SEABUS) integrating a local P3and a nonlocal P3are introduced.Approach. Specifically, the local P3enforces pixelwise edge-orientation consistency by conducting reference frame guided multiscale orientation projection on a subset containing a few adjacent frames; the nonlocal P3constrains the cubewise anatomic-structure similarity by performing cube matching and 4D filtering (CM4D) on all frames. By using effectively a composite splitting algorithm (CSA), SEABUS is incorporated into a fast iterative shrinkage-thresholding algorithm and a new accelerated CC-MRI approach named SEABUS-FCSA is proposed.Main results. The experiment and algorithm analysis demonstrate the efficiency and potential of the proposed SEABUS-FCSA approach, which has the best performance in terms of reducing aliasing artifacts and capturing dynamic features in comparison with several state-of-the-art accelerated CC-MRI technologies.Significance. Our approach aims to propose a new hybrid P3based iterative algorithm, which is not only used to improve the quality of accelerated cardiac cine imaging but also extend the FCSA methodology.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
彭于晏应助兰斯洛特117采纳,获得10
2秒前
平淡青烟完成签到,获得积分10
3秒前
Bonaventure发布了新的文献求助30
5秒前
5秒前
踏实之柔完成签到,获得积分10
7秒前
狂奔的蜗牛完成签到,获得积分10
9秒前
10秒前
hrs发布了新的文献求助10
10秒前
ding应助认真向日葵采纳,获得10
13秒前
17秒前
dihou111发布了新的文献求助10
21秒前
21秒前
SciGPT应助允胖胖采纳,获得10
21秒前
赘婿应助自由寻冬采纳,获得10
22秒前
研友_Zzrx6Z发布了新的文献求助10
26秒前
Hello应助DDTT采纳,获得10
27秒前
27秒前
27秒前
干净的琦应助dihou111采纳,获得10
28秒前
CipherSage应助dihou111采纳,获得10
28秒前
桐桐应助洛希极限采纳,获得10
29秒前
31秒前
32秒前
lanso完成签到 ,获得积分10
32秒前
xiaoshi发布了新的文献求助30
32秒前
33秒前
33秒前
在水一方应助略略略采纳,获得10
34秒前
34秒前
自由寻冬发布了新的文献求助10
37秒前
钰小憨完成签到,获得积分10
38秒前
38秒前
帅b发布了新的文献求助10
39秒前
科研通AI2S应助无情的千山采纳,获得10
39秒前
整齐的慕卉应助Laskujgkjbvg采纳,获得10
39秒前
整齐的慕卉应助Laskujgkjbvg采纳,获得10
39秒前
整齐的慕卉应助Laskujgkjbvg采纳,获得10
39秒前
整齐的慕卉应助Laskujgkjbvg采纳,获得10
39秒前
整齐的慕卉应助Laskujgkjbvg采纳,获得10
39秒前
整齐的慕卉应助Laskujgkjbvg采纳,获得10
40秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work 500
Handbuch Trainingswissenschaft – Trainingslehre 500
Additive Manufacturing Design and Applications (ASM Handbook, Volume 24A) 500
Variations: A More Diverse Picture of Contemporary Art 400
Induction Heating and Heat Treatment (ASM Handbook, Volume 4C) 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7589786
求助须知:如何正确求助?哪些是违规求助? 9167364
关于积分的说明 19621841
捐赠科研通 7169206
什么是DOI,文献DOI怎么找? 3267130
关于科研通互助平台的介绍 2432050
邀请新用户注册赠送积分活动 2259348