Simultaneous motion estimation and image reconstruction (SMEIR) for 4D cone‐beam CT

计算机视觉 迭代重建 人工智能 锥束ct 运动估计 成像体模 图像质量 投影(关系代数) 计算机科学 混叠 数学 算法 图像(数学) 计算机断层摄影术 光学 物理 医学 放射科 欠采样
作者
Jing Wang,Xuejun Gu
出处
期刊:Medical Physics [Wiley]
卷期号:40 (10) 被引量:95
标识
DOI:10.1118/1.4821099
摘要

Purpose: Image reconstruction and motion model estimation in four‐dimensional cone‐beam CT (4D‐CBCT) are conventionally handled as two sequential steps. Due to the limited number of projections at each phase, the image quality of 4D‐CBCT is degraded by view aliasing artifacts, and the accuracy of subsequent motion modeling is decreased by the inferior 4D‐CBCT. The objective of this work is to enhance both the image quality of 4D‐CBCT and the accuracy of motion model estimation with a novel strategy enabling simultaneous motion estimation and image reconstruction (SMEIR). Methods: The proposed SMEIR algorithm consists of two alternating steps: (1) model‐based iterative image reconstruction to obtain a motion‐compensated primary CBCT (m‐pCBCT) and (2) motion model estimation to obtain an optimal set of deformation vector fields (DVFs) between the m‐pCBCT and other 4D‐CBCT phases. The motion‐compensated image reconstruction is based on the simultaneous algebraic reconstruction technique (SART) coupled with total variation minimization. During the forward‐ and backprojection of SART, measured projections from an entire set of 4D‐CBCT are used for reconstruction of the m‐pCBCT by utilizing the updated DVF. The DVF is estimated by matching the forward projection of the deformed m‐pCBCT and measured projections of other phases of 4D‐CBCT. The performance of the SMEIR algorithm is quantitatively evaluated on a 4D NCAT phantom. The quality of reconstructed 4D images and the accuracy of tumor motion trajectory are assessed by comparing with those resulting from conventional sequential 4D‐CBCT reconstructions (FDK and total variation minimization) and motion estimation (demons algorithm). The performance of the SMEIR algorithm is further evaluated by reconstructing a lung cancer patient 4D‐CBCT. Results: Image quality of 4D‐CBCT is greatly improved by the SMEIR algorithm in both phantom and patient studies. When all projections are used to reconstruct a 3D‐CBCT by FDK, motion‐blurring artifacts are present, leading to a 24.4% relative reconstruction error in the NACT phantom. View aliasing artifacts are present in 4D‐CBCT reconstructed by FDK from 20 projections, with a relative error of 32.1%. When total variation minimization is used to reconstruct 4D‐CBCT, the relative error is 18.9%. Image quality of 4D‐CBCT is substantially improved by using the SMEIR algorithm and relative error is reduced to 7.6%. The maximum error (MaxE) of tumor motion determined from the DVF obtained by demons registration on a FDK‐reconstructed 4D‐CBCT is 3.0, 2.3, and 7.1 mm along left–right (L‐R), anterior–posterior (A‐P), and superior–inferior (S‐I) directions, respectively. From the DVF obtained by demons registration on 4D‐CBCT reconstructed by total variation minimization, the MaxE of tumor motion is reduced to 1.5, 0.5, and 5.5 mm along L‐R, A‐P, and S‐I directions. From the DVF estimated by SMEIR algorithm, the MaxE of tumor motion is further reduced to 0.8, 0.4, and 1.5 mm along L‐R, A‐P, and S‐I directions, respectively. Conclusions: The proposed SMEIR algorithm is able to estimate a motion model and reconstruct motion‐compensated 4D‐CBCT. The SMEIR algorithm improves image reconstruction accuracy of 4D‐CBCT and tumor motion trajectory estimation accuracy as compared to conventional sequential 4D‐CBCT reconstruction and motion estimation.
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
PDF的下载单位、IP信息已删除 (2025-6-4)

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
1秒前
liuyf完成签到 ,获得积分10
1秒前
3秒前
3秒前
YJ888发布了新的文献求助10
3秒前
今后应助Lu采纳,获得10
3秒前
EED发布了新的文献求助10
3秒前
88C真是太神奇啦完成签到,获得积分10
4秒前
4秒前
Rondab应助shuyi采纳,获得30
5秒前
酷酷飞烟发布了新的文献求助10
6秒前
7秒前
在水一方应助故意的靳采纳,获得50
8秒前
10秒前
忧郁的鱿鱼完成签到,获得积分10
10秒前
JamesPei应助lm采纳,获得10
12秒前
xww完成签到,获得积分10
12秒前
隐形曼青应助忐忑的阑香采纳,获得10
13秒前
秋半梦发布了新的文献求助10
14秒前
slp完成签到,获得积分20
21秒前
秋半梦完成签到,获得积分10
24秒前
bububusbu完成签到,获得积分10
24秒前
量子星尘发布了新的文献求助10
25秒前
我是老大应助TTm采纳,获得20
26秒前
科研通AI5应助Bressanone采纳,获得10
26秒前
坡坡大王发布了新的文献求助10
27秒前
华仔应助anna采纳,获得10
31秒前
carlin完成签到,获得积分10
33秒前
白子双完成签到,获得积分10
37秒前
FXQ123_范完成签到,获得积分10
37秒前
传奇3应助ran123456采纳,获得30
38秒前
keyan_baby完成签到,获得积分20
39秒前
41秒前
坡坡大王完成签到,获得积分10
42秒前
钱宇成关注了科研通微信公众号
42秒前
43秒前
Zayro完成签到,获得积分10
44秒前
45秒前
自信雅琴发布了新的文献求助10
45秒前
anna发布了新的文献求助10
48秒前
高分求助中
A new approach to the extrapolation of accelerated life test data 1000
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 500
‘Unruly’ Children: Historical Fieldnotes and Learning Morality in a Taiwan Village (New Departures in Anthropology) 400
Indomethacinのヒトにおける経皮吸収 400
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
基于可调谐半导体激光吸收光谱技术泄漏气体检测系统的研究 350
Robot-supported joining of reinforcement textiles with one-sided sewing heads 320
热门求助领域 (近24小时)
化学 材料科学 医学 生物 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 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3989115
求助须知:如何正确求助?哪些是违规求助? 3531367
关于积分的说明 11253688
捐赠科研通 3269986
什么是DOI,文献DOI怎么找? 1804868
邀请新用户注册赠送积分活动 882078
科研通“疑难数据库(出版商)”最低求助积分说明 809105