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
诺颜爱完成签到,获得积分10
刚刚
Lance发布了新的文献求助10
刚刚
Watermanlil发布了新的文献求助10
1秒前
none完成签到,获得积分10
2秒前
王一生完成签到,获得积分10
3秒前
诺颜爱发布了新的文献求助10
3秒前
隐形曼青应助张平安采纳,获得10
5秒前
qingqiu发布了新的文献求助10
6秒前
Copyright应助lash采纳,获得10
6秒前
8秒前
四宝完成签到 ,获得积分10
8秒前
今后应助jy采纳,获得10
8秒前
Wri完成签到,获得积分10
9秒前
11秒前
HUNTING完成签到 ,获得积分10
13秒前
15秒前
所所应助从容冷安采纳,获得10
16秒前
无花果应助黄焖鸡米饭采纳,获得10
17秒前
17秒前
夏思芫完成签到,获得积分10
18秒前
20秒前
jy发布了新的文献求助10
21秒前
22秒前
4tre44完成签到 ,获得积分10
24秒前
adgn发布了新的文献求助10
26秒前
小强x完成签到 ,获得积分10
29秒前
31秒前
31秒前
32秒前
嘉言懿行magnolia完成签到 ,获得积分10
33秒前
35秒前
37秒前
38秒前
7even完成签到,获得积分10
38秒前
霸气忙内发布了新的文献求助20
39秒前
彭于晏应助qingqiu采纳,获得10
39秒前
橙汁肉发布了新的文献求助20
40秒前
41秒前
Virginkiller1984完成签到 ,获得积分10
42秒前
42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
2026年中国辛酸癸酸聚乙二醇甘油酯行业市场现状调查及投资机会研判报告 1000
2026年中国辛酸癸酸聚乙二醇甘油酯行业市场规模及竞争格局分析报告 1000
48V Low-voltage Power Distribution Network (PDN) Architecture Industry Report, 2024 800
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 700
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
适配Micro-LED色转换的高兼容性量子点负性光刻胶制备与工艺研究 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 7317052
求助须知:如何正确求助?哪些是违规求助? 8932953
关于积分的说明 18937020
捐赠科研通 6976832
什么是DOI,文献DOI怎么找? 3214135
关于科研通互助平台的介绍 2382037
邀请新用户注册赠送积分活动 2193001