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1.
Article in Chinese | WPRIM | ID: wpr-986970

ABSTRACT

OBJECTIVE@#To propose a semi-supervised material quantitative intelligent imaging algorithm based on prior information perception learning (SLMD-Net) to improve the quality and precision of spectral CT imaging.@*METHODS@#The algorithm includes a supervised and a self- supervised submodule. In the supervised submodule, the mapping relationship between low and high signal-to-noise ratio (SNR) data was constructed through mean square error loss function learning based on a small labeled dataset. In the self- supervised sub-module, an image recovery model was utilized to construct the loss function incorporating the prior information from a large unlabeled low SNR basic material image dataset, and the total variation (TV) model was used to to characterize the prior information of the images. The two submodules were combined to form the SLMD-Net method, and pre-clinical simulation data were used to validate the feasibility and effectiveness of the algorithm.@*RESULTS@#Compared with the traditional model-driven quantitative imaging methods (FBP-DI, PWLS-PCG, and E3DTV), data-driven supervised-learning-based quantitative imaging methods (SUMD-Net and BFCNN), a material quantitative imaging method based on unsupervised learning (UNTV-Net) and semi-supervised learning-based cycle consistent generative adversarial network (Semi-CycleGAN), the proposed SLMD-Net method had better performance in both visual and quantitative assessments. For quantitative imaging of water and bone materials, the SLMD-Net method had the highest PSNR index (31.82 and 29.06), the highest FSIM index (0.95 and 0.90), and the lowest RMSE index (0.03 and 0.02), respectively) and achieved significantly higher image quality scores than the other 7 material decomposition methods (P < 0.05). The material quantitative imaging performance of SLMD-Net was close to that of the supervised network SUMD-Net trained with labeled data with a doubled size.@*CONCLUSIONS@#A small labeled dataset and a large unlabeled low SNR material image dataset can be fully used to suppress noise amplification and artifacts in basic material decomposition in spectral CT and reduce the dependence on labeled data-driven network, which considers more realistic scenario in clinics.


Subject(s)
Tomography, X-Ray Computed/methods , Image Processing, Computer-Assisted/methods , Algorithms , Signal-To-Noise Ratio , Perception
2.
Article in Chinese | WPRIM | ID: wpr-987039

ABSTRACT

OBJECTIVE@#To propose a diffusion tensor field estimation network based on 3D U-Net and diffusion tensor imaging (DTI) model constraint (3D DTI-Unet) to accurately estimate DTI quantification parameters from a small number of diffusion-weighted (DW) images with a low signal-to-noise ratio.@*METHODS@#The input of 3D DTI-Unet was noisy diffusion magnetic resonance imaging (dMRI) data containing one non-DW image and 6 DW images with different diffusion coding directions. The noise-reduced non-DW image and accurate diffusion tensor field were predicted through 3D U-Net. The dMRI data were reconstructed using the DTI model and compared with the true value of dMRI data to optimize the network and ensure the consistency of the dMRI data with the physical model of the diffusion tensor field. We compared 3D DTI-Unet with two DW image denoising algorithms (MP-PCA and GL-HOSVD) to verify the effect of the proposed method.@*RESULTS@#The proposed method was better than MP-PCA and GL-HOSVD in terms of quantitative results and visual evaluation of DW images, diffusion tensor field and DTI quantification parameters.@*CONCLUSION@#The proposed method can obtain accurate DTI quantification parameters from one non-DW image and 6 DW images to reduce image acquisition time and improve the reliability of quantitative diagnosis.


Subject(s)
Diffusion Tensor Imaging , Reproducibility of Results , Diffusion Magnetic Resonance Imaging , Algorithms , Signal-To-Noise Ratio
3.
Zhongguo yi xue ke xue yuan xue bao ; Zhongguo yi xue ke xue yuan xue bao;(6): 280-284, 2023.
Article in Chinese | WPRIM | ID: wpr-981264

ABSTRACT

Objective To explore the optimal parameters for virtual mono-energetic imaging of liver solid lesions. Methods A retrospective analysis was performed on 60 patients undergoing contrast-enhanced spectral CT of the abdomen.The iodine concentration values of hepatic arterial phase images and the CT values of different mono-energetic images were measured.The correlation coefficient and coefficient of variation were calculated. Results The average correlation coefficients between iodine concentrations and CT values of hepatic solid lesion images at 40,45,50,55,60,65,and 70 keV were 0.996,0.995,0.993,0.989,0.978,0.970,and 0.961,respectively.The correlation coefficients at 40(P=0.007),45(P=0.022),50 keV (P=0.035)were higher than that at 55 keV,and the correlation coefficients at 40 keV(P=0.134) and 45 keV(P=0.368) had no significant differences from that at 50 keV.The coefficients of variation of the CT values at 40,45,and 50 keV were 0.146,0.154,and 0.163,respectively. Conclusion The energy of 40 keV is optimal for virtual mono-energetic imaging of liver solid lesions in the late arterial phase,which is helpful for the diagnosis of liver diseases.


Subject(s)
Humans , Tomography, X-Ray Computed , Retrospective Studies , Abdomen , Iodine , Liver/diagnostic imaging , Signal-To-Noise Ratio , Radiographic Image Interpretation, Computer-Assisted/methods
4.
Zhongguo yi xue ke xue yuan xue bao ; Zhongguo yi xue ke xue yuan xue bao;(6): 416-421, 2023.
Article in Chinese | WPRIM | ID: wpr-981285

ABSTRACT

Objective To evaluate the impact of deep learning reconstruction algorithm on the image quality of head and neck CT angiography (CTA) at 100 kVp. Methods CT scanning was performed at 100 kVp for the 37 patients who underwent head and neck CTA in PUMC Hospital from March to April in 2021.Four sets of images were reconstructed by three-dimensional adaptive iterative dose reduction (AIDR 3D) and advanced intelligent Clear-IQ engine (AiCE) (low,medium,and high intensity algorithms),respectively.The average CT value,standard deviation (SD),signal-to-noise ratio (SNR),and contrast-to-noise ratio (CNR) of the region of interest in the transverse section image were calculated.Furthermore,the four sets of sagittal maximum intensity projection images of the anterior cerebral artery were scored (1 point:poor,5 points:excellent). Results The SNR and CNR showed differences in the images reconstructed by AiCE (low,medium,and high intensity) and AIDR 3D (all P<0.01).The quality scores of the image reconstructed by AiCE (low,medium,and high intensity) and AIDR 3D were 4.78±0.41,4.92±0.27,4.97±0.16,and 3.92±0.27,respectively,which showed statistically significant differences (all P<0.001). Conclusion AiCE outperformed AIDR 3D in reconstructing the images of head and neck CTA at 100 kVp,being capable of improving image quality and applicable in clinical examinations.


Subject(s)
Humans , Computed Tomography Angiography/methods , Radiation Dosage , Deep Learning , Radiographic Image Interpretation, Computer-Assisted/methods , Signal-To-Noise Ratio , Algorithms
5.
Article in English | WPRIM | ID: wpr-971372

ABSTRACT

OBJECTIVES@#Magnetic resonance diffusion-weighted imaging (DWI) has important clinical value in diagnosis and curative effect evaluation on endometrial carcinoma. How to improve the detection rate of endometrial small lesions by DWI is the research focus of MRI technology. This study aims to analyze the image quality of small field MRI ZOOMit-DWI sequence and conventional single-shot echo-planar imaging (SS-EPI) DWI sequence in the scanning of endometrial carcinoma, and to explore the clinical value of ZOOMit-DWI sequence.@*METHODS@#A total of 37 patients with endometrial carcinoma diagnosed by operation and pathology in the Second Xiangya Hospital of Central South University from July 2019 to May 2021 were collected. All patients were scanned with MRI ZOOMit-DWI sequence and SS-EPI DWI sequence before operation. Two radiologists subjectively evaluated the anatomical details, artifacts, geometric deformation and focus definition of the 2 groups of DWI images. At the same time, the signal intensity were measured and the signal-to-noise ratio (SNR), contrast to noise ratio (CNR), and apparent diffusion coefficient (ADC) of the 2 DWI sequences were calculated for objective evaluation. The differences of subjective score, objective score and ADC value of the 2 DWI sequences were analyzed.@*RESULTS@#The SNR of the ZOOMit-DWI group was significantly higher than that of the SS-EPI DWI group (301.96±141.85 vs 94.66±41.26), and the CNR of the ZOOMit-DWI group was significantly higher than that of the SS-EPI DWI group (185.05±105.45 vs 57.91±31.54, P<0.05). There was no significant difference in noise standard deviation between the ZOOMit-DWI group and the SS-EPI DWI group (P>0.05). The subjective score of anatomical detail and focus definition in the ZOOMit-DWI group was significantly higher than that of the SS-EPI DWI group (both P<0.05). The subjective score of artifacts and geometric deformation of ZOOMit-DWI group was significantly lower than that of the SS-EPI DWI group (both P<0.05). ADC had no significant difference between the ZOOMit-DWI group and the SS-EPI DWI group (P>0.05).@*CONCLUSIONS@#The image quality of ZOOMit-DWI is significantly higher than that of conventional SS-EPI DWI. In the MRI DWI examination of endometrial carcinoma, ZOOMit-DWI can effectively reduce the geometric deformation and artifacts of the image, which is more conducive to clinical diagnosis and treatment.


Subject(s)
Female , Humans , Signal-To-Noise Ratio , Endometrial Neoplasms/diagnostic imaging , Diffusion Magnetic Resonance Imaging/methods , Endometrium , Echo-Planar Imaging/methods , Reproducibility of Results
6.
J. biomed. eng ; Sheng wu yi xue gong cheng xue za zhi;(6): 409-417, 2023.
Article in Chinese | WPRIM | ID: wpr-981557

ABSTRACT

High-frequency steady-state asymmetric visual evoked potential (SSaVEP) provides a new paradigm for designing comfortable and practical brain-computer interface (BCI) systems. However, due to the weak amplitude and strong noise of high-frequency signals, it is of great significance to study how to enhance their signal features. In this study, a 30 Hz high-frequency visual stimulus was used, and the peripheral visual field was equally divided into eight annular sectors. Eight kinds of annular sector pairs were selected based on the mapping relationship of visual space onto the primary visual cortex (V1), and three phases (in-phase[0º, 0º], anti-phase [0º, 180º], and anti-phase [180º, 0º]) were designed for each annular sector pair to explore response intensity and signal-to-noise ratio under phase modulation. A total of 8 healthy subjects were recruited in the experiment. The results showed that three annular sector pairs exhibited significant differences in SSaVEP features under phase modulation at 30 Hz high-frequency stimulation. And the spatial feature analysis showed that the two types of features of the annular sector pair in the lower visual field were significantly higher than those in the upper visual field. This study further used the filter bank and ensemble task-related component analysis to calculate the classification accuracy of annular sector pairs under three-phase modulations, and the average accuracy was up to 91.5%, which proved that the phase-modulated SSaVEP features could be used to encode high- frequency SSaVEP. In summary, the results of this study provide new ideas for enhancing the features of high-frequency SSaVEP signals and expanding the instruction set of the traditional steady state visual evoked potential paradigm.


Subject(s)
Humans , Evoked Potentials, Visual , Brain-Computer Interfaces , Healthy Volunteers , Signal-To-Noise Ratio
7.
Article in Chinese | WPRIM | ID: wpr-936369

ABSTRACT

OBJECTIVE@#To propose a nonlocal spectral similarity-induced material decomposition network (NSSD-Net) to reduce the correlation noise in the low-dose spectral CT decomposed images.@*METHODS@#We first built a model-driven iterative decomposition model for dual-energy CT, optimized the objective function solving process using the iterative shrinking threshold algorithm (ISTA), and cast the ISTA decomposition model into the deep learning network. We then developed a novel cost function based on the nonlocal spectral similarity to constrain the training process. To validate the decomposition performance, we established a material decomposition dataset by real patient dual-energy CT data. The NSSD-Net was compared with two traditional model-driven material decomposition methods, one data-based material decomposition method and one data-model coupling-driven material decomposition supervised learning method.@*RESULTS@#The quantitative results showed that compared with the two traditional methods, the NSSD-Net method obtained the highest PNSR values (31.383 and 31.444) and SSIM values (0.970 and 0.963) and the lowest RMSE values (2.901 and 1.633). Compared with the datamodel coupling-driven supervised decomposition method, the NSSD-Net method obtained the highest SSIM values on water and bone decomposed results. The results of subjective image quality assessment by clinical experts showed that the NSSD-Net achieved the highest image quality assessment scores on water and bone basis material (8.625 and 8.250), showing significant differences from the other 4 decomposition methods (P < 0.001).@*CONCLUSION@#The proposed method can achieve high-precision material decomposition and avoid training data quality issues and model unexplainable issues.


Subject(s)
Humans , Algorithms , Image Processing, Computer-Assisted/methods , Phantoms, Imaging , Signal-To-Noise Ratio , Tomography, X-Ray Computed/methods , Water
8.
Zhongguo Yi Liao Qi Xie Za Zhi ; (6): 404-407, 2022.
Article in Chinese | WPRIM | ID: wpr-939756

ABSTRACT

This study introduces a portable multi-channel EEG signal acquisition system. The system is mainly composed of EEG electrode connector, signal conditioning circuit, EEG acquisition part, main control MCU and power supply part. The low-power EEG acquisition front-end ADS1299 and STM32 are used to form the signal acquisition and data communication part. The collected EEG signal can be transmitted to the PC for real-time display. After relevant tests, the system has small volume, low power consumption, high signal-to-noise ratio, and meets the requirements of portable wearable medical devices.


Subject(s)
Electric Power Supplies , Electrodes , Electroencephalography , Signal Processing, Computer-Assisted , Signal-To-Noise Ratio
9.
J. biomed. eng ; Sheng wu yi xue gong cheng xue za zhi;(6): 311-319, 2022.
Article in Chinese | WPRIM | ID: wpr-928227

ABSTRACT

Heart sound signal is a kind of physiological signal with nonlinear and nonstationary features. In order to improve the accuracy and efficiency of the phonocardiogram (PCG) classification, a new method was proposed by means of support vector machine (SVM) in which the complete ensemble empirical modal decomposition with adaptive noise (CEEMDAN) permutation entropy was as the eigenvector of heart sound signal. Firstly, the PCG was decomposed by CEEMDAN into a number of intrinsic mode functions (IMFs) from high to low frequency. Secondly, the IMFs were sifted according to the correlation coefficient, energy factor and signal-to-noise ratio. Then the instantaneous frequency was extracted by Hilbert transform, and its permutation entropy was constituted into eigenvector. Finally, the accuracy of the method was verified by using a hundred PCG samples selected from the 2016 PhysioNet/CinC Challenge. The results showed that the accuracy rate of the proposed method could reach up to 87%. In comparison with the traditional EMD and EEMD permutation entropy methods, the accuracy rate was increased by 18%-24%, which demonstrates the efficiency of the proposed method.


Subject(s)
Entropy , Heart Sounds , Signal Processing, Computer-Assisted , Signal-To-Noise Ratio , Support Vector Machine
10.
Zhongguo Yi Liao Qi Xie Za Zhi ; (6): 152-155, 2022.
Article in Chinese | WPRIM | ID: wpr-928877

ABSTRACT

This paper analyzes the shortcomings of the existing pure tone audiometers, and proposes a system to realize pure tone audiometry and speech audiometry with a new DSP processor. The pure tone test signal produced by the system has accurate frequency, high signal-to-noise ratio, and small harmonic distortion. The noise generator that comes with DSP adds a band-pass filter to realize the generation of narrow-band noise. At the same time, due to the modular structure of software design, the system has good ease of use and scalability. The test results show that the hearing test system has excellent performance and can be better used in hearing medical diagnosis.


Subject(s)
Audiometry, Pure-Tone/methods , Hearing , Noise , Signal-To-Noise Ratio
11.
Zhongguo Yi Liao Qi Xie Za Zhi ; (6): 248-253, 2022.
Article in Chinese | WPRIM | ID: wpr-928898

ABSTRACT

To solve the problem of real-time detection and removal of EEG signal noise in anesthesia depth monitoring, we proposed an adaptive EEG signal noise detection and removal method. This method uses discrete wavelet transform to extract the low-frequency energy and high-frequency energy of a segment of EEG signals, and sets two sets of thresholds for the low-frequency band and high-frequency band of the EEG signal. These two sets of thresholds can be updated adaptively according to the energy situation of the most recent EEG signal. Finally, we judge the level of signal interference according to the range of low-frequency energy and high-frequency energy, and perform corresponding denoising processing. The results show that the method can more accurately detect and remove the noise interference in the EEG signal, and improve the stability of the calculated characteristic parameters.


Subject(s)
Algorithms , Electroencephalography , Signal Processing, Computer-Assisted , Signal-To-Noise Ratio , Wavelet Analysis
12.
Zhongguo yi xue ke xue yuan xue bao ; Zhongguo yi xue ke xue yuan xue bao;(6): 47-52, 2021.
Article in Chinese | WPRIM | ID: wpr-878697

ABSTRACT

Objective To determine the appropriate averaging strategy for pancreatic perfusion datasets to create images for routine reading of insulinoma.Methods Thirty-nine patients undergoing pancreatic perfusion CT in Peking Union Medical College Hospital and diagnosed as insulinoma by pathology were enrolled in this retrospective study.The time-density curve of abdominal aorta calculated by software dynamic angio was used to decide the timings for averaging.Five strategies,by averaging 3,5,7,9 and 11 dynamic scans in perfusion,all including peak enhancement of the abdominal aorta,were investigated in the study.The image noise,pancreas signal-to-noise ratio(SNR),lesion contrast and lesion contrast-to-noise ratio(CNR)were recorded and compared.Besides,overall image quality and insulinoma depiction were also compared.ANOVA and Friedman's test were performed.Results The image noise decreased and the SNR of pancreas increased with the increase in averaging time points(all P0.99)and were higher than that of the first group(all P<0.05).There was no significant difference in overall image quality among the 5 groups(P=0.977).Conclusions Image averaged from 5 scans showed moderate image noise,pancreas SNR and relatively high lesion contrast and lesion CNR.Therefore,it is advised to be used in image averaging to detect insulinoma.


Subject(s)
Humans , Contrast Media , Insulinoma/diagnostic imaging , Pancreas/diagnostic imaging , Pancreatic Neoplasms/diagnostic imaging , Perfusion , Radiographic Image Interpretation, Computer-Assisted , Reading , Retrospective Studies , Signal-To-Noise Ratio
13.
Beijing Da Xue Xue Bao ; (6): 425-433, 2021.
Article in Chinese | WPRIM | ID: wpr-942197

ABSTRACT

Cryo-electron microscopy (cryo-EM) imaging has the unique potential to bridge the gap between cellular and molecular biology. Therefore, cryo-EM three-dimensional (3D) reconstruction has been rapidly developed in recent several years and applied widely in life science research to reveal the structures of large macromolecular assemblies and cellular complexes, which is critical to understanding their functions at all scales. Although the technical breakthrough in recent years, for example, the introduction of the direct detection device (DDD) camera and the development of cryo-EM software tools, made the three cryo-EM pioneers share the 2017 Nobel Prize, several bottleneck problems still exist that hamper the further increase of the resolution of single-particle reconstruction and hold back the application of in situ subnanometer structure determination by cryo-tomography. Radiation damage is still the key limiting factor in cryo-EM. In order to minimize the radiation damage and preserve as much resolution as possible, the imaging conditions of a low dose and weak contrast make cryo-EM images extremely noisy with very low signal-to-noise ratios (SNR), generally about 0.1. The high noise will obscure the fine details in cryo-EM images or reconstructed maps. Thus, a method to reduce the level of noise and improve the resolution has become an important issue. In this paper, we systematically reviewed and compared some robust filters in the cryo-EM field of two aspects, single-particle analysis (SPA) and cryo-electron tomography (cryo-ET), and especially studied their applications, such as, 3D reconstruction, visualization, structural analysis, and interpretation. Conventional approaches to noise reduction in cryo-EM imaging include the use of Gaussian, median, and bilateral filters, among other means. A Gaussian filter selects an appropriate filter kernel to conduct spatial convolution with a noisy image. Although noise with larger standard deviations in cryo-EM images can be suppressed and satisfactory performance is achieved in certain cases, this filter also blurs the images and over-smooths small-scale image features. This is especially detrimental when precise quantitative information needs to be extracted. Unlike a Gaussian filter, a median filter is based on the order statistics of the image and selects the median intensity in a window of the adjacent pixels to denoise the image. Although this filter is robust to outliers, it suffers from aliasing problems that possibly result in incorrect information for cryo-EM structure interpretation. A bilateral filter is a nonlinear filter that performs spatial weighted averaging and is more selective in the pixels allowing to contribute to the weighted sum, excluding the high frequency noise from the smoothing process. Thus, this filter can be used to smooth out noise while maintaining the edge details, which is similar to an anisotropic diffusion filter, and distinct from a Gaussian filter but its utility will be limited when the SNR of a cryo-EM image is very low. Generally, spatial filtering methods have the disadvantage of losing image resolution when reducing noise. A wavelet transform can exploit the wavelet's natural ability to separate a signal from noise at multiple image scales to allow for joint resolution in both the spatial and frequency domains, and thus has the potential to outperform existing methods. The modified wavelet shrinkage filter we developed can offer a remarkable improvement in image quality with a good compromise between detail preservation and noise smoothing. We expect that our review study on different filters can provide benefits to cryo-EM applications and the interpretation of biological structures.


Subject(s)
Algorithms , Cryoelectron Microscopy , Image Processing, Computer-Assisted , Normal Distribution , Signal-To-Noise Ratio , Tomography, X-Ray Computed
14.
Zhongguo yi xue ke xue yuan xue bao ; Zhongguo yi xue ke xue yuan xue bao;(6): 359-363, 2020.
Article in Chinese | WPRIM | ID: wpr-826356

ABSTRACT

To evaluate the effect of monochromatic energy image on inferior vena cava imaging quality on dual-layer detector spectral CT. Totally 39 patients who were clinically suspected of abdominal disease and referred to perform contrast-enhanced computed tomography(CT)were prospectively enrolled and underwent abdominal examination using a single-source,dual-detector spectral CT.The delayed phase scan was performed 3 minutes after injection of 60 ml of iopamidol(320 mg/ml)at a rate of 3 ml/s.The raw images were reconstructed to obtain conventional mixed energy images and spectral based images(SBI).The 40,50,60,and 70 keV single energy images were obtained.The CT value,noise,and signal-to-noise(SNR)of inferior vena cava and the contrast-to-noise(CNR)of inferior vena cava relative to psoas major on conventional mixed energy images and the 40,50,60,70 keV single energy images were measured.The SNRs and CNRs on monoenergetic 40-70 keV images were compared with polychromatic 120 kVp images.ANOVA was used to compare the CT value,noise,SNR,and CNR among these five groups.The optimal monoenergetic image set was chosen. The differences in CT value,noise,SNR,CNR of inferior vena cava were statistically significant among five groups(all <0.05).The SNR and CNR in 40 keV group and 50 keV group were significantly higher than those in other groups(all <0.05).The SNR of 40 keV group was significantly higher than that of 50 keV group(=0.002).The CNR of 40 keV group was not statistical different compared with that of 50 keV group(=0.630). 40 keV is the optimal monoenergetic energy level for the inferior vena cava on dual-layer detector spectral CT and may be valuable for the diagnosis of inferior vena cava disease.


Subject(s)
Humans , Abdomen , Radiographic Image Interpretation, Computer-Assisted , Signal-To-Noise Ratio , Tomography, X-Ray Computed , Vena Cava, Inferior
15.
J. biomed. eng ; Sheng wu yi xue gong cheng xue za zhi;(6): 271-279, 2020.
Article in Chinese | WPRIM | ID: wpr-828170

ABSTRACT

Spike recorded by multi-channel microelectrode array is very weak and susceptible to interference, whose noisy characteristic affects the accuracy of spike detection. Aiming at the independent white noise, correlation noise and colored noise in the process of spike detection, combining principal component analysis (PCA), wavelet analysis and adaptive time-frequency analysis, a new denoising method (PCWE) that combines PCA-wavelet (PCAW) and ensemble empirical mode decomposition is proposed. Firstly, the principal component was extracted and removed as correlation noise using PCA. Then the wavelet-threshold method was used to remove the independent white noise. Finally, EEMD was used to decompose the noise into the intrinsic modal function of each layer and remove the colored noise. The simulation results showed that PCWE can increase the signal-to-noise ratio by about 2.67 dB and decrease the standard deviation by about 0.4 μV, which apparently improved the accuracy of spike detection. The results of measured data showed that PCWE can increase the signal-to-noise ratio by about 1.33 dB and reduce the standard deviation by about 18.33 μV, which showed its good denoising performance. The results of this study suggests that PCWE can improve the reliability of spike signal and provide an accurate and effective spike denoising new method for the encoding and decoding of neural signal.


Subject(s)
Algorithms , Microelectrodes , Principal Component Analysis , Reproducibility of Results , Signal Processing, Computer-Assisted , Signal-To-Noise Ratio , Wavelet Analysis
16.
J. biomed. eng ; Sheng wu yi xue gong cheng xue za zhi;(6): 775-785, 2020.
Article in Chinese | WPRIM | ID: wpr-879204

ABSTRACT

Denoising methods based on wavelet analysis and empirical mode decomposition cannot essentially track and eliminate noise, which usually cause distortion of heart sounds. Based on this problem, a heart sound denoising method based on improved minimum control recursive average and optimally modified log-spectral amplitude is proposed in this paper. The proposed method uses a short-time window to smoothly and dynamically track and estimate the minimum noise value. The noise estimation results are used to obtain the optimal spectrum gain function, and to minimize the noise by minimizing the difference between the clean heart sound and the estimated clean heart sound. In addition, combined with the subjective analysis of spectrum and the objective analysis of contribution to normal and abnormal heart sound classification system, we propose a more rigorous evaluation mechanism. The experimental results show that the proposed method effectively improves the time-frequency features, and obtains higher scores in the normal and abnormal heart sound classification systems. The proposed method can help medical workers to improve the accuracy of their diagnosis, and also has great reference value for the construction and application of computer-aided diagnosis system.


Subject(s)
Humans , Algorithms , Heart Sounds , Signal Processing, Computer-Assisted , Signal-To-Noise Ratio , Wavelet Analysis
17.
Article in English | WPRIM | ID: wpr-1010536

ABSTRACT

To investigate associations between central visual function and inner retinal structure in primary open-angle glaucoma (POAG). This study enrolled 78 POAG patients and 58 healthy controls. POAG was classified into early glaucoma and moderate to advanced glaucoma. The following tests were performed on all participants: isolated-check visual evoked potential (icVEP) testing, 24-2 standard automated perimetry (SAP), and Cirrus optical coherence tomography (OCT) examinations. Signal-to-noise ratio (SNR) measures obtained from icVEP responses to isolated checks presented at four depths of modulation (DOMs; 8%, 14%, 22%, and 32%) were explored. Mean macular sensitivity (mMS) was assessed by calculating the mean sensitivities of central 12 SAP points. Ganglion cell layer+ inner plexiform layer thickness (GCL+IPLT) and peripapillary retinal nerve fiber layer thickness (pRNFLT) were measured by OCT scanning. For each group of subjects, linear relationships among the following measures were analyzed: SNR, mMS, GCL+IPLT, and pRNFLT. SNR, mMS, GCL+IPLT, and pRNFLT were all more significantly decreased in glaucoma than in controls (P<0.001). A significant positive association was found between SNR at 14% DOM and GCL+IPLT at the inferior sector in early glaucoma (r=0.465, P=0.004). In moderate to advanced glaucoma, significant correlations were found between SNR at 32% DOM and mean GCL+IPLT (r=0.364, P=0.023), superior GCL+IPLT (r=0.358, P=0.025), and mean pRNFLT (r=0.396, P=0.025). In addition, in moderate to advanced glaucoma, there were significant correlations between mMS and all relevant measures of retinal thickness (r=0.330-0.663, P< 0.010). In early glaucoma, significant correlations were found between mean mMS and minimum GCL+IPLT (r=0.373, P=0.023), and between inferior mMS and superior GCL+IPLT (r=0.470, P=0.003). Linear models provided a good explanation for the relationship between SNR and inner retinal thickness (IRT), whereas nonlinear models better explained the relationship between mMS and IRT. In early glaucoma, both SNR and mMS were related moderately and significantly to IRT, whereas in moderate to advanced glaucoma, mMS was more strongly correlated with IRT than SNR.


Subject(s)
Adult , Aged , Female , Humans , Male , Middle Aged , Evoked Potentials, Visual/physiology , Glaucoma, Open-Angle/physiopathology , Macula Lutea/physiopathology , Retina/physiopathology , Signal-To-Noise Ratio , Tomography, Optical Coherence
18.
CoDAS ; 32(5): e20180272, 2020. tab
Article in Portuguese | LILACS | ID: biblio-1133524

ABSTRACT

RESUMO Objetivo: Validar o conteúdo de um instrumento para mensuração do esforço auditivo para indivíduos com perda auditiva. Método: Trata-se de um estudo de validação, desenvolvido em duas fases, sendo a fase 1 o planejamento e desenvolvimento da primeira versão do instrumento e a fase 2 a investigação das evidências de validade baseadas no conteúdo do instrumento e desenvolvimento da versão final para mensuração de esforço auditivo. Participaram dez profissionais com expertise na área audiológica, com mais de cinco anos de experiência. O instrumento a ser validado foi composto por três partes: I - "percepção de fala de logatomas e esforço auditivo"; II - "esforço auditivo e memória operacional"; e III - "percepção de sentenças sem sentido e memória operacional", apresentadas de forma monoaural no silêncio e nas relações sinal-ruído +5dB, 0dB e -5dB. Foi realizada a análise descritiva das sugestões do comitê de fonoaudiólogos e do índice de validade de conteúdo individual e total. Resultados: Os resultados mostraram que as partes I e III do instrumento proposto atingiram o índice de validade de conteúdo total acima de 0,78, ou seja, os itens apresentados não necessitaram de modificações em seu constructo. Conclusão: As evidências de validade estudadas permitiram relevantes modificações e tornaram esse instrumento adequado ao seu constructo.


ABSTRACT Purpose: To validate the content of an instrument to measure listening effort for hearing-impaired individuals. Method: This is a validation study, developed in two stages, which the Stage 1 is the planning and development of the first version of the instrument, and Stage 2 the investigation of the evidences of validity based on the content and development of the final version of the instrument to measure listening effort. Ten professionals with expertise in the field of audiology, with more than five years of clinical experience participated in this study. The instrument to be validated was composed of three parts: I - "speech perception of logatomes and listening effort"; II - "listening effort and working memory" and; III - "speech perception of meaningless sentences and working memory" and they were presented monoaurally, in quiet and in the signal-to-noise ratios + 5dB, 0dB and -5dB. It was conducted a descriptive analysis regarding the suggestions of the committee judge audiologists and the analysis of the individual and scale content validity index. Results: The results showed that parts I and III which constitute the proposed instrument reached a scale content validity index above 0.78, which means that the presented items did not need modification in their construct. Conclusion: The evidences of validity studied allowed relevant modifications and made this instrument adequate to its construct.


Subject(s)
Humans , Speech Perception , Persons With Hearing Impairments , Auditory Perception , Signal-To-Noise Ratio , Memory, Short-Term
19.
Article in English | WPRIM | ID: wpr-786470

ABSTRACT

PURPOSE: Recently, a new Bayesian Penalized Likelihood (BPL) Reconstruction Algorithm was introduced by GE Healthcare, Q.Clear; it promises to provide better PET image resolution compared to the widely used Ordered Subset Expectation Maximization (OSEM). The aimof this study is to compare the performance of these two algorithms on several types of findings, in terms of image quality, lesion detectability, sensitivity, and specificity.METHODS: Between September 6th 2017 and July 31st 2018, 663 whole body 18F-FDG PET/CT scans were performed at the Nuclear Medicine Department of S. Martino Hospital (Belluno, Italy). Based on the availability of clinical/radiological follow-up data, 240 scans were retrospectively reviewed. For each scan, a hypermetabolic finding was selected, reporting both for OSEM and Q.Clear: SUVmax and SUVmean values of the finding, the liver and the background close to the finding; size of the finding; percentage variations of SUVmax and SUVmean. Each finding was subsequently correlated with clinical and radiological follow-up, to define its benign/malignant nature.RESULTS: Overall, Q.Clear improved the SUVvalues in each scan, especially in small findings (< 10mm), high SUVmax values (≥ 10), and medium/low backgrounds. Furthermore, Q.Clear amplifies the signal of hypermetabolic findings without modifying the background signal, which leads to an increase in signal-to-noise ratio, improving overall image quality. Finally, Q.Clear did not affect PET sensitivity or specificity, in terms of number of reported findings and characterization of their nature.CONCLUSIONS: Q.Clear is an iterative algorithm that improves significantly the quality of PET images compared to OSEM, increasing the SUVmax of findings (in particular for small findings) and the signal-to-noise ratio. However, due to the intrinsic characteristics of this algorithm, it will be necessary to adapt and/or modify the current interpretative criteria based of quantitative evaluation, to avoid an overestimation of the disease burden.


Subject(s)
Delivery of Health Care , Evaluation Studies as Topic , Fluorodeoxyglucose F18 , Follow-Up Studies , Liver , Nuclear Medicine , Positron Emission Tomography Computed Tomography , Retrospective Studies , Sensitivity and Specificity , Signal-To-Noise Ratio
20.
Article in English | WPRIM | ID: wpr-786499

ABSTRACT

PURPOSE: The treatment efficiency of ⁹⁰Y and providing reliable estimates of activity are evaluated by SPECT imaging of bremsstrahlung radiation released during beta therapy. In this technique, the resulting spectrum from ⁹⁰Y is very complex and continuous, which creates difficulties on the imaging protocol. Moreover, collimator geometry has an impressive effect on the spatial resolution, system sensitivity, image contrast, and the signal-to-noise ratio (SNR), which should be optimized.METHODS: We evaluated the effect of energy window width, reconstruction algorithms, and different geometries of a medium-energy (ME) parallel-hole collimator on the image contrast and SNR of ⁹⁰Y SPECT images. The Siemens E.Cam gamma camera equipped with a ME collimator and a digital Jaszczak phantom were simulated by SIMIND Monte Carlo program to generate the ⁹⁰Y bremsstrahlung SPECT images.RESULTS: Our results showed that optimal image quality can be acquired by the reconstruction algorithm of OS-EM in the energy window width of 60 to 400 keV for ⁹⁰Y bremsstrahlung SPECT imaging. Furthermore, the optimal values of the hole diameter and hole length of a ME collimator were obtained 0.235 and 4.4 cm, respectively.CONCLUSIONS: The acquired optimal ME collimator and energy window along with using a suitable reconstruction algorithm lead to improved contrast and SNR of ⁹⁰Y bremsstrahlung images of hot spheres of the digital Jaszczak phantom. This can improve the accuracy and precision of the ⁹⁰Y activity distribution estimation after radioembolization in targeted radionuclide therapy.


Subject(s)
Gamma Cameras , Signal-To-Noise Ratio , Tomography, Emission-Computed, Single-Photon
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