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地填写文献信息,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!

Synthetic digital reconstructed radiographs for MR-only robotic stereotactic radiation therapy: A proof of concept

基准标记 赛博刀 放射外科 计算机科学 人工智能 基本事实 图像配准 核医学 可视化 医学影像学 计算机视觉 医学 放射治疗 放射科 图像(数学)
作者
Gregory Szalkowski,Dong Nie,Tong Zhu,Pew‐Thian Yap,Jun Lian
出处
期刊:Computers in Biology and Medicine [Elsevier BV]
卷期号:138: 104917-104917 被引量:4
标识
DOI:10.1016/j.compbiomed.2021.104917
摘要

To create synthetic CTs and digital reconstructed radiographs (DRRs) from MR images that allow for fiducial visualization and accurate dose calculation for MR-only radiosurgery.We developed a machine learning model to create synthetic CTs from pelvic MRs for prostate treatments. This model has been previously proven to generate synthetic CTs with accuracy on par or better than alternate methods, such as atlas-based registration. Our dataset consisted of 11 paired CT and conventional MR (T2) images used for previous CyberKnife (Accuray, Inc) radiotherapy treatments. The MR images were pre-processed to mimic the appearance of fiducial-enhancing images. Two models were trained for each parameter case, using a sub-set of the available image pairs, with the remaining images set aside for testing and validation of the model to identify the optimal patch size and number of image pairs used for training. Four models were then trained using the identified parameters and used to generate synthetic CTs, which in turn were used to generate DRRs at angles 45° and 315°, as would be used for a CyberKnife treatment. The synthetic CTs and DRRs were compared visually and using the mean squared error and peak signal-to-noise ratio against the ground-truth images to evaluate their similarity.The synthetic CTs, as well as the DRRs generated from them, gave similar visualization of the fiducial markers in the prostate as the true counterparts. There was no significant difference found for the fiducial localization for the CTs and DRRs. Across the 8 DRRs analyzed, the mean MSE between the normalized true and synthetic DRRs was 0.66 ± 0.42% and the mean PSNR for this region was 22.9 ± 3.7 dB. For the full CTs, the mean MAE was 72.9 ± 88.1 HU and the mean PSNR was 31.2 ± 2.2 dB.Our machine learning-based method provides a proof of concept of a way to generate synthetic CTs and DRRs for accurate dose calculation and fiducial localization for use in radiation treatment of the prostate.

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
linuo完成签到,获得积分10
2秒前
ljz完成签到,获得积分20
2秒前
学霸宇大王完成签到 ,获得积分10
3秒前
知鱼之乐发布了新的文献求助10
3秒前
4秒前
5秒前
5秒前
mo完成签到,获得积分10
7秒前
俭朴的翠阳完成签到,获得积分10
8秒前
ljz发布了新的文献求助30
9秒前
风清发布了新的文献求助10
10秒前
njseu完成签到 ,获得积分10
11秒前
11秒前
mieyy完成签到,获得积分10
11秒前
乐乐应助lf采纳,获得10
11秒前
12秒前
12秒前
忧郁虔完成签到 ,获得积分20
12秒前
小萝卜完成签到 ,获得积分10
13秒前
傅立叶完成签到,获得积分10
16秒前
17秒前
17秒前
syh5527029发布了新的文献求助30
18秒前
18秒前
18秒前
lizishu应助99giddens采纳,获得200
19秒前
20秒前
21秒前
wangqinxin完成签到,获得积分10
22秒前
雪莉发布了新的文献求助10
23秒前
scutwqq发布了新的文献求助10
23秒前
万跑跑完成签到 ,获得积分10
24秒前
sparkling发布了新的文献求助10
24秒前
Ava应助温婉的友儿采纳,获得10
25秒前
lf发布了新的文献求助10
25秒前
大笨蛋应助NGC2244采纳,获得20
26秒前
27秒前
27秒前
ys关注了科研通微信公众号
28秒前
睁眼睡大觉完成签到 ,获得积分20
28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
Developing Genetic Editing Tools for Lysobacter 2000
卤化钙钛矿人工突触的研究 2000
Моделирование процессов самоорганизации в кристаллообразующих системах 1000
History of U.S. Space Surveillance and Satellite Cataloging 1000
Signals, Systems, and Signal Processing 610
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 600
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 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6518508
求助须知:如何正确求助?哪些是违规求助? 8311205
关于积分的说明 17768638
捐赠科研通 5620376
什么是DOI,文献DOI怎么找? 2926342
邀请新用户注册赠送积分活动 1903156
关于科研通互助平台的介绍 1763995