Evaluation of the novel 3D SPECT modelling algorithm in the STIR reconstruction framework: Simple vs. full attenuation correction

衰减 迭代重建 成像体模 投影(关系代数) 衰减校正 计算机科学 算法 噪音(视频) 像素 单光子发射计算机断层摄影术 探测器 光学 物理 人工智能 图像(数学) 核医学 医学
作者
Berta Martí-Fuster,Kjell Erlandsson,Carles Falcón,Charalampos Tsoumpas,Lefteris Livieratos,D. Ros,Kris Thielemans
标识
DOI:10.1109/nssmic.2013.6829258
摘要

A 3D SPECT system matrix modelling library has recently been incorporated into STIR - a software package for tomographic image reconstruction. The SPECT modelling accounts for the effects of attenuation and spatially variant resolution by incorporating them into the system matrix. Attenuation calculation can be done either along a single line (simple model), or along multiple lines for the various detector pixels covered by the PSF (full model). Due to practical reasons, a simple central-line approximation is often used for the attenuation modelling in SPECT. Our aim was to evaluate the effect of this approximation in the reconstructed images using STIR. A rotating SPECT system was modelled, equipped with different collimators. We generated noise-free projection data using the full model and reconstructed images using both models. We used a phantom consisting of an ellipse containing 4 spherical inserts with the same activity concentration but different attenuation coefficients. Images were reconstructed using the OS-MAP algorithm, 12 subsets and up to 100 iterations. With the simple model, the four spheres were all different in terms of intensity as well as distribution. When using the full attenuation model, all spheres appeared quite similar, independent of the attenuation. Our results show that the simple attenuation model can lead to artifacts and inaccurate quantification, while the full model adds significant accuracy and stability to the reconstructed images.
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
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
jies发布了新的文献求助10
1秒前
xuan发布了新的文献求助10
2秒前
河狸完成签到 ,获得积分10
2秒前
微宝完成签到,获得积分10
3秒前
隐形曼青应助随风守着她采纳,获得10
4秒前
4秒前
啊啊缘发布了新的文献求助10
4秒前
理杏仁应助阿豪要发文章采纳,获得10
5秒前
杀死一双玫瑰完成签到 ,获得积分10
5秒前
隐形曼青应助高俊飞采纳,获得10
5秒前
大个应助自觉的冬云采纳,获得10
6秒前
1111完成签到,获得积分10
6秒前
6秒前
7秒前
7秒前
昏睡的金毛完成签到,获得积分10
8秒前
8秒前
爆米花应助仁爱的觅风采纳,获得30
9秒前
xuan发布了新的文献求助10
9秒前
林少龙完成签到,获得积分10
9秒前
Li发布了新的文献求助10
9秒前
10秒前
徐乐完成签到 ,获得积分10
10秒前
12秒前
愉快的真发布了新的文献求助10
12秒前
lzcnextdoor发布了新的文献求助10
12秒前
CipherSage应助微笑向卉采纳,获得10
13秒前
领导范儿应助雨无意采纳,获得10
13秒前
15秒前
xuan发布了新的文献求助10
16秒前
16秒前
18秒前
李健应助番茄采纳,获得10
18秒前
18秒前
Light完成签到,获得积分10
19秒前
19秒前
果冻发布了新的文献求助10
19秒前
19秒前
20秒前
20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
Römisch-Germanische Forschungen 1000
APA handbook of comparative psychology: Basic concepts, methods, neural substrate, and behavior 1000
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The fast track to determining transfer functions of linear circuits: The student guide 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 500
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 7610277
求助须知:如何正确求助?哪些是违规求助? 9186003
关于积分的说明 19678549
捐赠科研通 7184002
什么是DOI,文献DOI怎么找? 3270360
关于科研通互助平台的介绍 2434021
邀请新用户注册赠送积分活动 2265047