scholarly journals Raman Signal Denoising Using Fully Convolutional Encoder Decoder Network

2022 ◽  
Author(s):  
Irem Loc ◽  
Ibrahim Kecoglu ◽  
Mehmet Burcin Unlu ◽  
Ugur Parlatan
Keyword(s):  
Raman Spectroscopy ◽  
Signal To Noise Ratio ◽  
Raman Signal ◽  
P Value ◽  
Signal To Noise ◽  
Tissue Samples ◽  
High Exposure ◽  
Noise Ratio ◽  
Living Tissues ◽  
Convolutional Encoder

Raman spectroscopy is a vibrational method that gives molecular information rapidly and non-invasively. Despite its advantages, the weak intensity of Raman spectroscopy leads to low-quality signals, particularly with tissue samples. The requirement of high exposure times makes Raman a time-consuming process and diminishes its non-invasive property while studying living tissues. Novel denoising techniques using convolutional neural networks (CNN) have achieved remarkable results in image processing. Here, we propose a similar approach for noise reduction for the Raman spectra acquired with 10x lower exposure times. In this work, we developed fully convolutional encoder-decoder architecture (FCED) and trained them with noisy Raman signals. The results demonstrate that our model is superior (p-value <0.0001) to the conventional denoising techniques such as the Savitzky-Golay filter and wavelet denoising. Improvement in the signal-to-noise ratio values ranges from 20% to 80%, depending on the initial signal-to-noise ratio. Thus, we proved that tissue analysis could be done in a shorter time without any need for instrumental enhancement.

scholarly journals Anode heel effect application with step wedge against effect of signal to noise ratio in computed radiography

2020 ◽  
Vol 4 (3) ◽  
pp. 75-82
Author(s):  
Ni Nyoman Ratini ◽  
I Made Yuliara ◽  
Windaryoto Windaryoto
Keyword(s):  
Computed Radiography ◽  
Signal To Noise Ratio ◽  
Pearson Correlation ◽  
P Value ◽  
Signal To Noise ◽  
Correlation Test ◽  
Pearson Correlation Test ◽  
R Value ◽  
Noise Ratio ◽  
Heel Effect

It was researched on the application of Anoda Heel Effect (AHE) with a step wedge on the effect of Signal To Noise Ratio (SNR) on Computed Radiography (CR) has been carried out. This research was conducted on a 21 step wedge with two treatments, namely the application of AHE and without the application of AHE. This measurement is repeated three times on radiographs to obtain a total image of six images (without the application of AHE as many as three images and with the application of AHE as many as three images). The results of taking radiographs using AHE and without AHE were measured using the RadiAnt Dicom Viewer program. The SNR value on the step wedge image without the AHE application has an average of 26.89. The SNR value on the step wedge image using AHE is 60.54. The results of the correlation test (Pearson correlation test) on the SNR showed that there was a significant and very strong effect of the application of AHE on the step wedge on the SNR in CR (p-value <0.001 and the R-value ranging from 0.600 to 0.799).

scholarly journals Analisis Perbandingan Nilai Signal to Noise Ratio (SNR) pada Pemeriksaan MRI Ankle Joint dengan Menggunakan Quad Knee Coil dan Flex/Multipurpose Coil

2017 ◽  
Vol 3 (1) ◽  
pp. 220-224
Author(s):  
Ahda Nur Arifah ◽  
Yeti Kartikasari ◽  
Emi Murniati
Keyword(s):  
Achilles Tendon ◽  
Ankle Joint ◽  
Subtalar Joint ◽  
Signal To Noise Ratio ◽  
P Value ◽  
Signal To Noise ◽  
Talocrural Joint ◽  
Knee Coil ◽  
Noise Ratio ◽  
Joint Examination

Background : Research on the difference comparison the value of Signal To Noise Ratio (SNR) at MRI Ankle Joint examination using Quad Knee Coil and Flex/Multipurpose Coil at the hospital's radiology installation Telogorejo Semarang. Quad knee coil is a volume coil, is a coil that can act as a transmitter and receiver at the same RF signal (transreceiver). Flex / Multipurpose Coil is a surface coil which has a high SNR for a superficial examination (a small organ). The purpose of this research is to know comparison the value of signal to noise ratio (SNR) and higher the value of signal to noise ratio (SNR) at MRI Ankle Joint examination using Quad Knee Coil and Flex / Multipurpose Coil.Method : This type of research is quantitative experimental approach. The research data which 6 samples. Rate includes images subjectively talocalcaneal interosseous ligament, talocrural joint, subtalar joint, the calcaneus, tibia, talus, and the Achilles tendon. Then the results of the data in Paired T-Test tested.Results : Test results that there are differences in comparison the value of signal to noise ratio (SNR) at MRI Ankle Joint examination using Quad Knee Coil and Flex / Multipurpose Coil which has a p-value / sig for all of 0.002, and each criterion that have talocalcaneal interoseous ligament p value 0.026, talocrural joint p value 0.017, subtalar joint p value 0.001, calcaneus p value 0.002, tibia p value 0.003, talus p value 0.006, and achilles tendon p value 0.012. This is in accordance with the calculated average value SNR on the use of Quad Knee Coil is higher at 110.67 because the coil acts as transreceiver and has two preamplifier so as to improve the SNRConclusion : There is a differences in comparison the value of Signal To Noise Ratio (SNR) at MRI Ankle Joint examination using Quad Knee Coil and Flex / Multipurpose Coil.

Signal-to-noise ratio of Raman signal measured by multichannel detectors

2021 ◽  
Author(s):  
Xue-Lu Liu ◽  
Yu-Chen Leng ◽  
Miao-Ling Lin ◽  
Xin Cong ◽  
Ping-Heng Tan
Keyword(s):  
Signal To Noise Ratio ◽  
Raman Signal ◽  
Signal To Noise ◽  
Noise Ratio

scholarly journals Super-Resolution Reconstruction of Cell Pseudo-Color Image Based on Raman Technology

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4076
Author(s):  
Yang ◽  
Zhu ◽  
Wang ◽  
Yang ◽  
Wu ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Raman Spectrum ◽  
Background Noise ◽  
Color Image ◽  
Signal To Noise Ratio ◽  
Super Resolution ◽  
Reconstruction Algorithm ◽  
Signal To Noise ◽  
Noise Ratio ◽  
Pseudo Color

Raman spectroscopy visualization is a challenging task due to the interference of complex background noise and the number of selected measurement points. In this paper, a super-resolution image reconstruction algorithm for Raman spectroscopy is studied to convert raw Raman data into pseudo-color super-resolution imaging. Firstly, the Raman spectrum data of a single measurement point is measured multiple times to calculate the mean value to remove the random background noise, and innovatively introduce the Retinex algorithm and the median filtering algorithm which improve the signal-to-noise ratio. The novel method of using deep neural network performs a super-resolution reconstruction operation on the gray image. An adaptive guided filter that automatically adjusts the filter radius and penalty factor is proposed to highlight the contour of the cell, and the super-resolution reconstruction of the pseudo-color image of the Raman spectrum is realized. The average signal-to-noise ratio of the reconstructed pseudo-color image sub-band reaches 14.29 db, and the average value of information entropy reaches 4.30 db. The results show that the Raman-based cell pseudo-color image super-resolution reconstruction algorithm is an effective tool to effectively remove noise and high-resolution visualization. The contrast experiments show that the pseudo-color image Kullback–Leiber (KL) entropy of the color image obtained by the method is small, the boundary is obvious, and the noise is small, which provide technical support for the development of sophisticated single-cell imaging Raman spectroscopy instruments.

Fluorescence photobleaching of urine for improved signal to noise ratio of the Raman signal – An exploratory study

2021 ◽  
Vol 247 ◽  
pp. 119144
Author(s):  
Surjendu Bikash Dutta ◽  
Hemant Krishna ◽  
Khan Mohammad Khan ◽  
Sharad Gupta ◽  
Shovan Kumar Majumder
Keyword(s):  
Exploratory Study ◽  
Signal To Noise Ratio ◽  
Raman Signal ◽  
Signal To Noise ◽  
Noise Ratio

Quantitative Raman Spectroscopy when the Signal-to-Noise is Below the Limit of Quantitation due to Fluorescence Interference: Advantages of a Moving Window Sequentially Shifted Excitation Approach

2016 ◽  
Vol 70 (9) ◽  
pp. 1489-1501 ◽  
Author(s):  
Sarah Marshall ◽  
John B. Cooper
Keyword(s):  
Raman Spectroscopy ◽  
Quantitative Analysis ◽  
Signal To Noise Ratio ◽  
Raman Signal ◽  
Moving Window ◽  
Linear Calibration ◽  
Signal To Noise ◽  
Raman Analysis ◽  
Binary Model ◽  
Limit Of Quantitation

Raman spectroscopy is a useful analytical tool. However, its application is often limited because shot noise from fluorescence obscures the Raman signal. In such cases, quantitative analysis is not possible when the signal-to-noise ratio (SNR) drops below two. A method is described for performing quantitative Raman spectroscopy that not only removes fluorescence backgrounds, but also results in a significant improvement in the SNR. The Raman data is extracted using a moving window sequentially shifted excitation algorithm. To demonstrate the capabilities of the method, a binary mixture of two analytes at varying concentrations is quantified in the presence of a highly fluorescent dye. Linear calibration plots were constructed and validated for the binary model using individual Raman peaks with SNR ranging from 0.073–12.6; r2 values are greater than 0.96 in all cases, with all but the weakest peaks yielding values greater than 0.997. The presented method demonstrates a universal and autonomous approach for the quantitative analysis of highly fluorescent samples via Raman spectroscopy. The lower limit on the SNR ratio for quantitative Raman analysis with the described method is 0.1. In order to assess the effectiveness of the presented method, the entire set of experiments was also processed using the more common shifted excitation Raman difference spectroscopy (SERDS) approach. The advantages of the proposed method over SERDS are demonstrated for both the detection limit and the SNR of the processed spectra.

scholarly journals Analisis Variasi Time Repetition (TR) terhadap Signal to Noise Ratio dan Contrast to Noise Ratio pada Pemeriksaan MRI Cervical T2 Weighted Fast Spin Echo (FSE) Potongan Sagital

2016 ◽  
Vol 2 (1) ◽  
pp. 119-123
Author(s):  
Rini Indrati ◽  
Heriansyah Heriansyah ◽  
Wakhrudin Wakhrudin
Keyword(s):  
Signal To Noise Ratio ◽  
Spin Echo ◽  
Fast Spin Echo ◽  
Mean Deviation ◽  
P Value ◽  
Signal To Noise ◽  
Mri Examination ◽  
Spin Echo Sequence ◽  
Noise Ratio ◽  
Fast Spin

Background: Time Repetition (TR) is one parameter that can affect the value of Signal to Noise Ratio (SNR) and Contrast to Noise Ratio (CNR). The purpose of this research is to know the effect of variation of TR value on SNR and CNR on cervical MRI examination with Sagital T2 Weighted Fast Spin Echo sequence and to know the most optimal TR value from the variation of TR value to SNR and CNR on cervical MRI examination with Sagital T2 Weighted Fast Spin Echo.Methods: The type of this study was experimental study. The study was conducted using MRI 1.5 Tesla at Kasih Ibu Denpasar Hospital. Data were 40 MRI cervical images of sagital Fast Spin Echo from 10 volunteers with four variations of TR (2500 ms, 3000 ms, 3500 ms, and 4000 ms). The SNR and CNR values are measured by identifying the Region of Interest (ROI) in the corpus, discus, cerebro spinal fluid (CSF), and medula spinalis regions to obtain the average signals and compared with the mean deviation of the background. Data was analyzed by regression test to know the influence and by Anova test.Results: The result of the research showed that there was the influence of TR value to SNR and CNR of MRI Cervical Sagital T2 FSE. There was a strong correlation between the variation of TR values with SNR and CNR Cervical with p-value 0.05, the optimal TR value obtained in Cervical Sagital T2 FSE anatomical image on MRI 1,5 Tesla modality was 3500 ms.Conclusion: Time Repetition affected the signal to noise ratio and contrast to noise ratio. TR 3500 ms produced the most optimal cervical MRI image quality.

scholarly journals Determination of best Raman spectroscopy spatial offsets for transcutaneous bone quality assessments in human hands

2021 ◽  
Author(s):  
Keren Chen ◽  
Christine Massie ◽  
Hani A Awad ◽  
Andrew J Berger
Keyword(s):  
Raman Spectroscopy ◽  
Bone Quality ◽  
Bone Fracture ◽  
Signal To Noise Ratio ◽  
Spectral Unmixing ◽  
Absolute Amount ◽  
Signal To Noise ◽  
Noise Ratio ◽  
Quality Assessments

Spatially offset Raman spectroscopy (SORS) is able to detect bone signal transcutaneously and could assist in predicting bone fracture risk. Criteria for optimal source-detector offsets for transcutaneous human measurements, however, are not well-established. Although larger offsets yield a higher percentage of bone signal, the absolute amount of bone signal decreases. Spectral unmixing into bone, adipose, and non-adipose components was employed to quantify changes in bone signal to noise ratio across a range of offsets, and optimal offsets for phalanx and metacarpal measurements were determined. The bone signal to noise ratio was maximized at offsets ranging from 4-6 mm.

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