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
Lucas应助efig采纳,获得10
1秒前
mwb完成签到,获得积分20
1秒前
搜集达人应助Ryan采纳,获得10
1秒前
jielo发布了新的文献求助10
1秒前
科研通AI6.4应助ly采纳,获得10
2秒前
Orange应助lbryd采纳,获得10
4秒前
Joyce发布了新的文献求助10
4秒前
5秒前
6秒前
6秒前
7秒前
小楚楚发布了新的文献求助10
8秒前
852应助helen采纳,获得10
8秒前
领导范儿应助seraphist采纳,获得10
9秒前
汉堡包应助Yolo采纳,获得10
9秒前
maple完成签到,获得积分10
9秒前
科研通AI6.4应助zj采纳,获得10
9秒前
冷静剑成完成签到,获得积分10
9秒前
10秒前
LiYanqin完成签到,获得积分10
10秒前
YB完成签到,获得积分10
12秒前
赘婿应助YURI采纳,获得10
12秒前
13秒前
叶艳完成签到 ,获得积分10
14秒前
远方传来风笛完成签到,获得积分10
14秒前
吗喽发布了新的文献求助10
15秒前
16秒前
17秒前
17秒前
小半完成签到,获得积分10
17秒前
18秒前
18秒前
装饰图图犬完成签到,获得积分10
19秒前
keysoz发布了新的文献求助10
19秒前
kuoping完成签到,获得积分0
19秒前
20秒前
guaxi发布了新的文献求助10
21秒前
小毛同学发布了新的文献求助10
21秒前
21秒前
感到蔚蓝发布了新的文献求助10
22秒前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(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
Gründe der Seele:Die Wiener Psychatrie im 20.Jahrhundert 1000
Development of a Bridge Weigh-In-Motion System: A technology to convert the bridge response to the passage of traffic into data on vehicle configurations, speeds, times of travel and weights 1000
Organic Reactions, Volume 116 1000
Current concepts in cutaneous toxicity : proceedings of the Fourth Conference on Cutaneous Toxicity, Washington, D.C., May 9-11, 1979 1000
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 7268279
求助须知:如何正确求助?哪些是违规求助? 8888982
关于积分的说明 18789544
捐赠科研通 6944714
什么是DOI,文献DOI怎么找? 3203533
关于科研通互助平台的介绍 2376329
邀请新用户注册赠送积分活动 2179333