已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整的填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

Deep Learning-Enhanced Parallel Imaging and Simultaneous Multislice Acceleration Reconstruction in Knee MRI

多层 磁共振成像 图像质量 核医学 医学 加速度 膝关节 计算机科学 人工智能 放射科 外科 物理 图像(数学) 经典力学
作者
MinWoo Kim,Sangmin Lee,Chankue Park,Dongeon Lee,Kang Soo Kim,Hee Seok Jeong,Shin-Young Kim,Min-Hyeok Choi,Dominik Nickel
出处
期刊:Investigative Radiology [Ovid Technologies (Wolters Kluwer)]
卷期号:57 (12): 826-833 被引量:24
标识
DOI:10.1097/rli.0000000000000900
摘要

This study aimed to examine various combinations of parallel imaging (PI) and simultaneous multislice (SMS) acceleration imaging using deep learning (DL)-enhanced and conventional reconstruction. The study also aimed at comparing the diagnostic performance of the various combinations in internal knee derangement and provided a quantitative evaluation of image sharpness and noise using edge rise distance (ERD) and noise power (NP), respectively.The data from adult patients who underwent knee magnetic resonance imaging using various DL-enhanced acquisitions between June 2021 and January 2022 were retrospectively analyzed. The participants underwent conventional 2-fold PI and DL protocols with 4- to 8-fold acceleration imaging (P2S2 [2-fold PI with 2-fold SMS], P3S2, and P4S2). Three readers evaluated the internal knee derangement and the overall image quality. The diagnostic performance was calculated using consensus reading as a standard reference, and we conducted comparative evaluations. We calculated the ERD and NP for quantitative evaluations of image sharpness and noise, respectively. Interreader and intermethod agreements were calculated using Fleiss κ.A total of 33 patients (mean age, 49 ± 19 years; 20 women) were included in this study. The diagnostic performance for internal knee derangement and the overall image quality were similar among the evaluated protocols. The NP values were significantly lower using the DL protocols than with conventional imaging ( P < 0.001), whereas the ERD values were similar among these methods ( P > 0.12). Interreader and intermethod agreements were moderate-to-excellent (κ = 0.574-0.838) and good-to-excellent (κ = 0.755-1.000), respectively. In addition, the mean acquisition time was reduced by 47% when using DL with P2S2, by 62% with P3S2, and by 71% with P4S2, compared with conventional P2 imaging (2 minutes and 55 seconds).The combined use of DL-enhanced 8-fold acceleration imaging (4-fold PI with 2-fold SMS) showed comparable performance with conventional 2-fold PI for the evaluation of internal knee derangement, with a 71% reduction in acquisition time.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

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
三杠完成签到 ,获得积分10
1秒前
勤劳的冰菱完成签到,获得积分10
1秒前
z21发布了新的文献求助10
2秒前
可乐应助想昵称太难了采纳,获得10
3秒前
酷酷草莓完成签到,获得积分10
3秒前
王蕊完成签到,获得积分10
7秒前
DY完成签到,获得积分10
9秒前
isonomia完成签到,获得积分10
9秒前
二牛完成签到,获得积分10
11秒前
结实的小土豆完成签到 ,获得积分10
12秒前
12秒前
12秒前
天水张家辉完成签到,获得积分10
13秒前
鲍文启完成签到,获得积分10
14秒前
kaiqiang完成签到,获得积分0
14秒前
两个榴莲完成签到,获得积分0
14秒前
独特的娩完成签到 ,获得积分10
14秒前
isonomia发布了新的文献求助200
14秒前
dyuguo3完成签到 ,获得积分10
16秒前
766465完成签到 ,获得积分10
17秒前
阿衍完成签到 ,获得积分10
17秒前
春山完成签到 ,获得积分10
17秒前
wang5945完成签到 ,获得积分10
17秒前
Lucas应助11采纳,获得10
18秒前
RTP完成签到 ,获得积分10
18秒前
meng完成签到 ,获得积分10
18秒前
鲍文启发布了新的文献求助30
19秒前
白天科室黑奴and晚上实验室牛马完成签到 ,获得积分10
20秒前
Akaashi完成签到,获得积分10
20秒前
小泰勒横着走完成签到,获得积分10
20秒前
喝可乐的萝卜兔完成签到 ,获得积分10
20秒前
悄悄完成签到 ,获得积分10
22秒前
z21完成签到,获得积分10
22秒前
22秒前
hg秀秀完成签到 ,获得积分10
23秒前
剑道尘心完成签到 ,获得积分10
26秒前
星禾吾发布了新的文献求助10
26秒前
wwf完成签到,获得积分10
27秒前
WYnini完成签到 ,获得积分10
27秒前
沉默毛豆发布了新的文献求助10
27秒前
高分求助中
Production Logging: Theoretical and Interpretive Elements 2000
Very-high-order BVD Schemes Using β-variable THINC Method 1200
BIOLOGY OF NON-CHORDATES 1000
进口的时尚——14世纪东方丝绸与意大利艺术 Imported Fashion:Oriental Silks and Italian Arts in the 14th Century 800
Autoregulatory progressive resistance exercise: linear versus a velocity-based flexible model 550
Education and Upward Social Mobility in China: Imagining Positive Sociology with Bourdieu 500
Zeitschrift für Orient-Archäologie 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 细胞生物学 免疫学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3353376
求助须知:如何正确求助?哪些是违规求助? 2978001
关于积分的说明 8683184
捐赠科研通 2659256
什么是DOI,文献DOI怎么找? 1456109
科研通“疑难数据库(出版商)”最低求助积分说明 674278
邀请新用户注册赠送积分活动 664978

今日热心研友

无情向薇
20
完美世界
10
可乐
10
星禾吾
1
小蘑菇
10
注:热心度 = 本日应助数 + 本日被采纳获取积分÷10