Stepwise method based on Wiener estimation for spectral reconstruction in spectroscopic Raman imaging

拉曼光谱 光学 光谱成像 迭代重建 材料科学 光谱带 核磁共振 物理 计算机科学 人工智能
作者
Shuo Chen,Gang Wang,Xiaoyu Cui,Quan Liu
出处
期刊:Optics Express [The Optical Society]
卷期号:25 (2): 1005-1005 被引量:36
标识
DOI:10.1364/oe.25.001005
摘要

Raman spectroscopy has demonstrated great potential in biomedical applications. However, spectroscopic Raman imaging is limited in the investigation of fast changing phenomena because of slow data acquisition. Our previous studies have indicated that spectroscopic Raman imaging can be significantly sped up using the approach of narrow-band imaging followed by spectral reconstruction. A multi-channel system was built to demonstrate the feasibility of fast wide-field spectroscopic Raman imaging using the approach of simultaneous narrow-band image acquisition followed by spectral reconstruction based on Wiener estimation in phantoms. To further improve the accuracy of reconstructed Raman spectra, we propose a stepwise spectral reconstruction method in this study, which can be combined with the earlier developed sequential weighted Wiener estimation to improve spectral reconstruction accuracy. The stepwise spectral reconstruction method first reconstructs the fluorescence background spectrum from narrow-band measurements and then the pure Raman narrow-band measurements can be estimated by subtracting the estimated fluorescence background from the overall narrow-band measurements. Thereafter, the pure Raman spectrum can be reconstructed from the estimated pure Raman narrow-band measurements. The result indicates that the stepwise spectral reconstruction method can improve spectral reconstruction accuracy significantly when combined with sequential weighted Wiener estimation, compared with the traditional Wiener estimation. In addition, qualitatively accurate cell Raman spectra were successfully reconstructed using the stepwise spectral reconstruction method from the narrow-band measurements acquired by a four-channel wide-field Raman spectroscopic imaging system. This method can potentially facilitate the adoption of spectroscopic Raman imaging to the investigation of fast changing phenomena.

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
leisure应助科研通管家采纳,获得10
刚刚
VDC应助科研通管家采纳,获得30
刚刚
liuaoo发布了新的文献求助10
刚刚
无花果应助科研通管家采纳,获得10
刚刚
小青椒应助科研通管家采纳,获得10
1秒前
求助人员应助科研通管家采纳,获得10
1秒前
1秒前
大模型应助科研通管家采纳,获得10
1秒前
自由寄柔发布了新的文献求助30
1秒前
wills应助科研通管家采纳,获得10
1秒前
Lucas应助科研通管家采纳,获得10
1秒前
Jasper应助蕾蕾大酱采纳,获得10
2秒前
李健的粉丝团团长应助周_采纳,获得10
2秒前
独特听芹完成签到,获得积分10
2秒前
Tan完成签到 ,获得积分10
2秒前
3秒前
4秒前
123发布了新的文献求助10
4秒前
华青ww完成签到,获得积分10
4秒前
王晓朋完成签到,获得积分10
4秒前
agd122完成签到,获得积分10
5秒前
5秒前
喝到几点完成签到,获得积分10
5秒前
英姑应助dd采纳,获得10
5秒前
邹万恶完成签到,获得积分10
5秒前
善学以致用应助苏silence采纳,获得10
5秒前
简单半邪完成签到,获得积分10
5秒前
库凯伊完成签到,获得积分10
6秒前
7秒前
piggybunny发布了新的文献求助10
7秒前
无情的踏歌完成签到,获得积分10
7秒前
深海鳕鱼完成签到,获得积分10
8秒前
8秒前
zz完成签到,获得积分10
9秒前
guozizi发布了新的文献求助50
9秒前
王王王完成签到,获得积分10
9秒前
9秒前
123完成签到,获得积分10
9秒前
永毅完成签到 ,获得积分10
9秒前
斯文败类应助夕荀采纳,获得10
10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
List of 1,091 Public Pension Profiles by Region 1621
Les Mantodea de Guyane: Insecta, Polyneoptera [The Mantids of French Guiana] | NHBS Field Guides & Natural History 1500
Lloyd's Register of Shipping's Approach to the Control of Incidents of Brittle Fracture in Ship Structures 1000
Brittle fracture in welded ships 1000
Metagames: Games about Games 700
King Tyrant 680
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5573946
求助须知:如何正确求助?哪些是违规求助? 4660289
关于积分的说明 14728668
捐赠科研通 4600067
什么是DOI,文献DOI怎么找? 2524676
邀请新用户注册赠送积分活动 1495011
关于科研通互助平台的介绍 1465006