Denoised and texture enhanced MVCT to improve soft tissue conspicuity

断层治疗 成像体模 人工智能 计算机视觉 降噪 对比度(视觉) 计算机科学 医学 核医学 放射科 放射治疗
作者
Ke Sheng,Shuiping Gou,Jiaolong Wu,X. Sharon Qi
出处
期刊:Medical Physics [Wiley]
卷期号:41 (10): 101916-101916 被引量:75
标识
DOI:10.1118/1.4894714
摘要

PURPOSE: MVCT images have been used in TomoTherapy treatment to align patients based on bony anatomies but its usefulness for soft tissue registration, delineation, and adaptive radiation therapy is limited due to insignificant photoelectric interaction components and the presence of noise resulting from low detector quantum efficiency of megavoltage x-rays. Algebraic reconstruction with sparsity regularizers as well as local denoising methods has not significantly improved the soft tissue conspicuity. The authors aim to utilize a nonlocal means denoising method and texture enhancement to recover the soft tissue information in MVCT (DeTECT). METHODS: A block matching 3D (BM3D) algorithm was adapted to reduce the noise while keeping the texture information of the MVCT images. Following imaging denoising, a saliency map was created to further enhance visual conspicuity of low contrast structures. In this study, BM3D and saliency maps were applied to MVCT images of a CT imaging quality phantom, a head and neck, and four prostate patients. Following these steps, the contrast-to-noise ratios (CNRs) were quantified. RESULTS: By applying BM3D denoising and saliency map, postprocessed MVCT images show remarkable improvements in imaging contrast without compromising resolution. For the head and neck patient, the difficult-to-see lymph nodes and vein in the carotid space in the original MVCT image became conspicuous in DeTECT. For the prostate patients, the ambiguous boundary between the bladder and the prostate in the original MVCT was clarified. The CNRs of phantom low contrast inserts were improved from 1.48 and 3.8 to 13.67 and 16.17, respectively. The CNRs of two regions-of-interest were improved from 1.5 and 3.17 to 3.14 and 15.76, respectively, for the head and neck patient. DeTECT also increased the CNR of prostate from 0.13 to 1.46 for the four prostate patients. The results are substantially better than a local denoising method using anisotropic diffusion. CONCLUSIONS: The authors showed that it is feasible to extract more soft tissue contrast information from the noisy MVCT images using a nonlocal means 3D block matching method in combination with saliency maps, revealing information that was originally unperceivable to human observers.
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
xiqiaoya应助Nothing采纳,获得10
刚刚
刚刚
宣以晴发布了新的文献求助10
刚刚
搜集达人应助hz132511采纳,获得10
1秒前
xiaxia完成签到,获得积分10
1秒前
1秒前
111完成签到,获得积分10
2秒前
健忘的城完成签到,获得积分10
2秒前
2秒前
2秒前
972676742发布了新的文献求助10
2秒前
Ecool关注了科研通微信公众号
2秒前
干净的琦发布了新的文献求助30
3秒前
CipherSage应助哇哇哇采纳,获得10
3秒前
烊驼发布了新的文献求助10
3秒前
3秒前
辛夷应助科研通管家采纳,获得10
3秒前
3秒前
酷波er应助科研通管家采纳,获得10
3秒前
慕青应助科研通管家采纳,获得10
3秒前
3秒前
脑洞疼应助科研通管家采纳,获得10
3秒前
x菜鸡博士应助科研通管家采纳,获得10
4秒前
汉堡包应助科研通管家采纳,获得30
4秒前
打打应助科研通管家采纳,获得10
4秒前
4秒前
x菜鸡博士应助科研通管家采纳,获得10
4秒前
陈花蕾发布了新的文献求助10
4秒前
bkagyin应助科研通管家采纳,获得10
4秒前
搜集达人应助科研通管家采纳,获得10
4秒前
小蘑菇应助科研通管家采纳,获得10
4秒前
所所应助科研通管家采纳,获得10
4秒前
酷波er应助科研通管家采纳,获得10
4秒前
Golden完成签到,获得积分10
4秒前
wanci应助科研通管家采纳,获得10
5秒前
科目三应助科研通管家采纳,获得10
5秒前
Owen应助科研通管家采纳,获得30
5秒前
科研通AI61应助科研通管家采纳,获得10
5秒前
5秒前
5秒前
高分求助中
Cronologia da história de Macau 5000
Erwählung und Berufung bei Paulus: Bedeutung, Entwicklung und Funktion einer Vorstellung in ihrem frühjüdischen und griechisch-römischen Kontext 850
Matrix Methods in Data Mining and Pattern Recognition 510
Interactions of Vowel Quality and Prosody in East Slavic 500
用于植入式医疗器械的馈通设计与实现 400
Animalia: Animal and Human Interaction in the Early Medieval English World (Exeter Studies in Medieval Europe) 400
Synfacts Issue 07 · Volume 22 400
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 7134607
求助须知:如何正确求助?哪些是违规求助? 8783987
关于积分的说明 18569588
捐赠科研通 6719806
什么是DOI,文献DOI怎么找? 3153440
关于科研通互助平台的介绍 2278884
邀请新用户注册赠送积分活动 2127773