Automatic wavelet-based retinal blood vessels segmentation and vessel diameter estimation

Automatic detection of retinal blood vessels and measurement of vessel diameter are important steps in the computer aided diagnosis in ophthalmology. Here, we present a new multi-scale vessel enhancement method based on complex continuous wavelet transform (CCWT). The parameters of CCWT are optimized to represent line structures in all directions and separate them from simple edges. The final vessel network is obtained by applying an adaptive histogram-based thresholding process along with a proper length filtering method. An efficient circular structure operator is employed on the centerline of vessels to estimate their diameters. The performance of the proposed method is measured on the publicly available DRIVE and STARE databases and compared with several state-of-the-art methods as well as second observer. The proposed method shows much higher accuracy (95%) and sensitivity (79%) in the same range of specificity (97%). The predictive value of it is higher than 72.9%. The vessel diameter estimation process also shows lower root mean square error compared to the existing methods and second observer.     

Computationally Efficient Cosine Modulated Filter Bank Design for ECG Signal Compression

In this work, computationally efficient and reliable cosine modulated filter banks (CMFBs) are designed for Electrocardiogram (ECG) data compression. First of all, CMFBs (uniform and non-uniform) are designed using interpolated finite impulse response (IFIR) prototype filter to reduce the computational complexity. To reduce the reconstruction error, linear iteration technique is applied to optimize the prototype filter. Then after, non-uniform CMFB is used for ECG data compression by decomposing ECG signal into various frequency bands. Subsequently, thresholding is applied for truncating the insignificant coefficients. The estimation of the threshold value is done by examining the significant energy of each band. Further, Run-length encoding (RLE) is utilized for improving the compression performance. The method is applied to MIT-BIH arrhythmia database for performance analysis of the proposed work. The experimental observations demonstrate that the proposed method has accomplished high compression ratio with the admirable quality of signal reconstruction. The proposed work provides the average values of compression ratio (CR), percent root mean square difference (PRD), percent root mean square difference normalized (PRDN), quality score (QS), correlation coefficient (CC), maximum error (ME), mean square error (MSE), and signal to noise ratio (SNR) are 23.86, 1.405, 2.55, 19.08, 0.999, 0.12, 0.054 and 37.611 dB, respectively. The proposed 8-channel uniform filter bank is used to detect the R-peak locations of the ECG signal. The comparative analysis shows that beats (locations and amplitudes) of both signals (original and reconstructed signals) are same.     

Wavelet energy based diagnostic distortion measure for ECG

In this paper, a novel Wavelet Energy based diagnostic distortion (WEDD) measure is proposed to assess the reconstructed signal quality for ECG compression algorithms. WEDD is evaluated from the Wavelet coefficients of the original and the reconstructed ECG signals. For each ECG segment, a Wavelet energy weight vector is computed via five-level biorthogonal discrete Wavelet transform (DWT). WEDD is defined as the sum of Wavelet energy weighted percentage root mean square difference of each subband. The effectiveness of this measure is validated by linear (linear polynomial and cubic polynomial) and nonlinear (logistic) regression analysis between the computed WEDD values and the mean opinion score (MOS) given by cardiologists. WEDD provides a better prediction accuracy and exhibits a statistically better monotonic relationship with the MOS ratings than Wavelet based weighted percentage root mean square difference (PRD) measure (WWPRD), PRD and other objective measures. Standard correlation coefficient and Spearman rank-order correlation coefficient (SROCC) between the WEDD/MOS ratings is 0.969 and 0.9624, respectively.     

Analysis of ECG signal denoising method based on S-transform

Electrocardiogram (ECG), a noninvasive technique which is used generally as a primary diagnostic tool for cardiovascular diseases. A cleaned ECG signal provides necessary information about the electrophysiology of the heart diseases and ischemic changes that may occur. However in real situation, noise is often embedded with ECG signal during acquisition. In this paper, a novel ECG signal denoising technique is proposed using Stockwell transform (S-transform). This method is evaluated on several normal and abnormal ECG signals of MIT/BIH arrhythmia database, by artificially adding white Gaussian noises to visually inspected clean ECG recordings. The experimental results demonstrate that the proposed method shows the better signal to noise ratio (SNR), lower root mean square error (RMSE) and percent root mean square difference (PRD) compared to generally used ECG denoising method like wavelet transform.     

基于近红外光谱技术的白茶可溶性糖总量快速测定研究

本文以积分球漫反射模块采集113份不同等级不同年份的白茶近红外光谱图并进行预处理分析,采用蒽酮比色法对来自不同厂家的白茶进行含量测定,运用偏最小二乘法(PLS)建立了白茶可溶性糖总量快速测定模型并对模型进行验证。试验结果表明所建立模型的相关系数(R)为0. 963,校正均方根差(RMSEC)为0. 363 9,验证均方根差(RMSEP)为0. 349,验证集平均相对误差为3. 11%。通过NIRS快速测定白茶总糖含量具有较高的可行性,该方法预测结果较好,能够准确、快速、无损的对白茶可溶性糖总量进行快速定量分析。     

A Morphological Hessian Based Approach for Retinal Blood Vessels Segmentation and Denoising Using Region Based Otsu Thresholding

Diabetic Retinopathy (DR) harm retinal blood vessels in the eye causing visual deficiency. The appearance and structure of blood vessels in retinal images play an essential part in the diagnoses of an eye sicknesses. We proposed a less computational unsupervised automated technique with promising results for detection of retinal vasculature by using morphological hessian based approach and region based Otsu thresholding. Contrast Limited Adaptive Histogram Equalization (CLAHE) and morphological filters have been used for enhancement and to remove low frequency noise or geometrical objects, respectively. The hessian matrix and eigenvalues approach used has been in a modified form at two different scales to extract wide and thin vessel enhanced images separately. Otsu thresholding has been further applied in a novel way to classify vessel and non-vessel pixels from both enhanced images. Finally, postprocessing steps has been used to eliminate the unwanted region/segment, non-vessel pixels, disease abnormalities and noise, to obtain a final segmented image. The proposed technique has been analyzed on the openly accessible DRIVE (Digital Retinal Images for Vessel Extraction) and STARE (STructured Analysis of the REtina) databases along with the ground truth data that has been precisely marked by the experts.     

Novel method for measurement of medium size arterial lumen area with an impedance catheter: in vivo validation

There is no doubt that the transformation of a cardiac catheter into a conductance catheter that allows reliable and accurate assessment of lumen cross-sectional area (CSA) will provide a powerful diagnostic and treatment tool for the invasive cardiologist. The objective of this study was to develop a method based on the impedance catheter that allows accurate and reproducible measurements of CSA for medium size vessels (e.g., coronary, femoral, and carotid arteries). Two solutions of NaCl (0.5% and 1.5%) with known conductivities were injected directly into the lumen of the artery in eight swine. We showed that the CSA can be determined analytically from two Ohm's law-type algebraic equations that account for the parallel conductance of the current into the surrounding tissue. Excellent agreement was found between the conductance catheter with the proposed two-injection method and B-mode ultrasound (US). The root mean square error for the impedance measurements was 4.8% of the mean US diameter. The repeatability of the technique was assessed with duplicate measurements. The mean of the difference between the two measurements was nearly zero, and the repeatability coefficient was within 2.4% of the mean of the two measurements. The validated method was used to assess the degree of acute vasodilatation of the vessel in response to flow overload.     

Unsupervised Retinal Vessel Segmentation Using Combined Filters

Image segmentation of retinal blood vessels is a process that can help to predict and diagnose cardiovascular related diseases, such as hypertension and diabetes, which are known to affect the retinal blood vessels’ appearance. This work proposes an unsupervised method for the segmentation of retinal vessels images using a combined matched filter, Frangi’s filter and Gabor Wavelet filter to enhance the images. The combination of these three filters in order to improve the segmentation is the main motivation of this work. We investigate two approaches to perform the filter combination: weighted mean and median ranking. Segmentation methods are tested after the vessel enhancement. Enhanced images with median ranking are segmented using a simple threshold criterion. Two segmentation procedures are applied when considering enhanced retinal images using the weighted mean approach. The first method is based on deformable models and the second uses fuzzy C-means for the image segmentation. The procedure is evaluated using two public image databases, Drive and Stare. The experimental results demonstrate that the proposed methods perform well for vessel segmentation in comparison with state-of-the-art methods.     

Evaluation of the kinetic energy of the torso by magneto-inertial measurement unit during the sit-to-stand movement

Sit-to-stand tests are used in geriatrics as a qualitative issue in order to evaluate motor control and stability. In terms of measured indicators, it is traditionally the duration of the task that is reported, however it appears that the use of the kinetic energy as a new quantitative criterion allows getting a better understanding of musculoskeletal deficits of elderly subjects. The aim of this study was to determine the feasibility to obtain the measure of kinetic energy using magneto-inertial measurement units (MIMU) during sit-to-stand movements at various paces. 26 healthy subjects contributed to this investigation. Measured results were compared to a marker-based motion capture using the correlation coefficient and the normalized root mean square error (nRMSE). nRMSE were below 10% and correlation coefficients were over 0.97. In addition, errors on the mean kinetic energy were also investigated using Bland-Altman 95% limits of agreement (0.63 J–0.77 J), RMSE (0.29 J–0.38 J) and correlation coefficient (0.96–0.98). The results obtained highlighted that the method based on MIMU data could be an alternative to optoelectronic data acquisition to assess the kinetic energy of the torso during the sit-to-stand test, suggesting this method as being a promising alternative to determine kinetic energy during the sit-to-stand movement.     

ECG Data Compression Using Modified Run Length Encoding of Wavelet Coefficients for Holter Monitoring

ObjectiveIn cardiac patient-care, compression of long-term ECG data is essential to minimize the data storage requirement and transmission cost. Hence, this paper presents a novel electrocardiogram data compression technique which utilizes modified run-length encoding of wavelet coefficients.MethodFirst, wavelet transform is applied to the ECG data which decomposes it and packs maximum energy to less number of transform coefficients. The wavelet transform coefficients are quantized using dead-zone quantization. It discards small valued coefficients lying in the dead-zone interval while other coefficients are kept at the formulated quantized output interval. Among all the quantized coefficients, an average value is assigned to those coefficients for which energy packing efficiency is less than 99.99%. The obtained coefficients are encoded using modified run-length coding. It offers higher compression ratio than conventional run-length coding without any loss of information.ResultsCompression performance of the proposed technique is evaluated using different ECG records taken from the MIT-BIH arrhythmia database. The average compression performance in terms of compression ratio, percent root mean square difference, normalized percent mean square difference, and signal to noise ratio are 17.18, 3.92, 6.36, and 28.27 dB respectively for 48 ECG records.ConclusionThe compression results obtained by the proposed technique is better than techniques recently introduced by others. The proposed technique can be utilized for compression of ECG records of Holter monitoring.     

小波分析在人血清中葡萄糖短波近红外定量中的应用

利用小波分析对13名志愿者18个血清样品的短波近红外光谱进行去噪预处理,以血糖仪测定的血糖为参考,采用间隔偏最小二乘法（iPLS）在700nm～1060nm短波近红外波段建立血糖浓度预测模型。由相关系数（R）和预测标准差（RMSEP）对预测模型的精确度进行了评价。预测模型的相关系数为0．9654,均方根预测误差为0．2435,并和采用傅立叶变换去噪方法及iPLS建模的结果进行了比较。结果表明：小波分析预处理数据的方法能更有效地扣除噪声干扰,使模型具有更强的抗干扰能力和更高的预测精度。     

Retinal Vessel Segmentation: An Efficient Graph Cut Approach with Retinex and Local Phase

Our application concerns the automated detection of vessels in retinal images to improve understanding of the disease mechanism, diagnosis and treatment of retinal and a number of systemic diseases. We propose a new framework for segmenting retinal vasculatures with much improved accuracy and efficiency. The proposed framework consists of three technical components: Retinex-based image inhomogeneity correction, local phase-based vessel enhancement and graph cut-based active contour segmentation. These procedures are applied in the following order. Underpinned by the Retinex theory, the inhomogeneity correction step aims to address challenges presented by the image intensity inhomogeneities, and the relatively low contrast of thin vessels compared to the background. The local phase enhancement technique is employed to enhance vessels for its superiority in preserving the vessel edges. The graph cut-based active contour method is used for its efficiency and effectiveness in segmenting the vessels from the enhanced images using the local phase filter. We have demonstrated its performance by applying it to four public retinal image datasets (3 datasets of color fundus photography and 1 of fluorescein angiography). Statistical analysis demonstrates that each component of the framework can provide the level of performance expected. The proposed framework is compared with widely used unsupervised and supervised methods, showing that the overall framework outperforms its competitors. For example, the achieved sensitivity (0:744), specificity (0:978) and accuracy (0:953) for the DRIVE dataset are very close to those of the manual annotations obtained by the second observer.     

A novel method for blood vessel detection from retinal images

Background  

The morphological changes of the retinal blood vessels in retinal images are important indicators for diseases like diabetes, hypertension and glaucoma. Thus the accurate segmentation of blood vessel is of diagnostic value.     

怀地黄叶片中总环烯醚萜苷及总苯乙醇苷含量快速分析模型的建立

本文旨在建立地黄叶片中总环烯醚萜苷及苯乙醇苷定量分析模型。利用紫外-可见分光光度法测定不同种质怀地黄生育期内的128份地黄叶片中总环烯醚萜苷及总苯乙醇苷的含量,并将其作为基础值,结合地黄叶片的近红外光谱图,利用TQ8.0分析软件结合偏最小二乘法(PLS),分别建立地黄叶片中总环烯醚萜苷及总苯乙醇苷的定量分析模型。地黄叶片中总苯乙醇苷定量校正模型决定系数(R2)为0.998 2,校正均方根偏差(RMSEC)为0.089 9,预测均方决定差(RMSEP)为0.142,交叉验证均方根偏差(RMSECV)为0.707 2;总环烯醚萜苷定量校正模型的内部交叉验证决定系数(R2)为0.972 1,校正均方差(RMSEC)为0.259,预测均方决定差(RMSEP)为0.095 4,交叉验证均方根偏差(RMSECV)为0.869 4。预测值与实测值差异无统计学意义。该定量模型可用于怀地黄叶片中总环烯醚萜苷及总苯乙醇苷含量的快速测定。     

Compensation for Retinal Vessel Density Reduces the Variation of Circumpapillary RNFL in Healthy Subjects

This work intends to assess circumpapillary retinal vessel density (RVD) at a 3.46 mm diameter circle and correlate it with circumpapillary retinal nerve fiber layer (RNFL) thickness measured with Fourier-Domain Optical Coherence Tomography. Furthermore, it aims to evaluate the reduction of intersubject variability of RNFL when considering RVD as a source of information for RNFL distribution. For that, 106 healthy subjects underwent circumpapillary RNFL measurement. Using the scanning laser ophthalmoscope fundus image, thickness and position of retinal vessels were assessed and integrated in a 256-sector RVD profile. The relationship between local RVD value and local RNFL thickness was modeled by linear regression. RNFL was then compensated for RVD variation by regression formulas. A strong statistically significant intrasubject correlation was found for all subjects between RVD and RNFL profiles (mean R = 0.769). In the intersubject regression analysis, 247 of 256 RNFL sectors showed a statistically significant positive correlation with RVD (mean R = 0.423). RVD compensation of RNFL resulted in a relative reduction of up to 20% of the intersubject variance. In conclusion, RVD in a 3.46mm circle has a clinically relevant influence on the RNFL distribution. RVD may be used to develop more individualized normative values for RNFL measurement, which might improve early diagnosis of glaucoma.     

Online monitoring of horseradish peroxidase structural changes by Near Infrared (NIR) Spectroscopy

The development of online monitoring techniques is of great relevance for understanding the structural changes of proteins under different conditions in order to maximize their catalytic activity. This study aimed to evaluate the potential of the NIR (near-infrared spectroscopy) technique for the monitoring of alterations of secondary and tertiary structures of Horseradish peroxidase (HRP), an oxidoreductase that has several applications in the industrial environment, food industry and bioremediation. The NIR associated to the multivariate calibration, through the PLS (partial least square) method allowed the construction of a robust model for the prediction of the analysis. The values of the correlation coefficient (R²), root mean square error of calibration (RMSEC), root mean square error of prediction (RMSEP) and root mean square error of cross validation (RMSECV) for secondary structure analysis using circular dichroism (CD) data as reference (actual values) were 0.9681, 0.647 (mdeg), 0.945 (mdeg), and 1.12 (mdeg), respectively. For tertiary structure analysis, fluorescence spectroscopy (FL) data were used as reference. R², RMSEC, RMSEP and RMSECV were, respectively 0.9999, 1.95 (a.u.), 2.09 (a.u.); and 2.19 (a.u.). NIR combined multivariate calibration showed promising results for sctructural changes monitoring of HRP.     

Estimating the complete ground reaction forces with pressure insoles in walking

This study presented a method to estimate the complete ground reaction forces from pressure insoles in walking. Five male subjects performed 10 walking trials in a laboratory. The complete ground reaction forces were collected during a right foot stride by a force plate at 1000Hz. Simultaneous plantar pressure data were collected at 100Hz by a pressure insole system with 99 sensors covering the whole plantar area. Stepwise linear regressions were performed to individually reconstruct the complete ground reaction forces in three directions from the 99 individual pressure data until redundancy among the predictors occurred. An additional linear regression was performed to reconstruct the vertical ground reaction force by the sum of the value of the 99 pressure sensors. Five other subjects performed the same walking test for validation. Estimated ground reaction forces in three directions were calculated with the developed regression models, and were compared with the real data recorded from force plate. Accuracy was represented by the correlation coefficient and the root mean square error. Results showed very good correlation in anterior-posterior (0.928) and vertical (0.989) directions, and reasonable correlation in medial-lateral direction (0.719). The root mean square error was about 12%, 5% and 28% of the peak recorded value. Future studies should aim to generalize the methods or to establish specific methods to other subjects, patients, motions, footwear and floor conditions. The method gives an extra option to study an estimation of the complete ground reaction forces in any environment without the constraints from the number and location of force plates.     

A Robust Post-Processing Workflow for Datasets with Motion Artifacts in Diffusion Kurtosis Imaging

Purpose

The aim of this study was to develop a robust post-processing workflow for motion-corrupted datasets in diffusion kurtosis imaging (DKI).

Materials and methods

The proposed workflow consisted of brain extraction, rigid registration, distortion correction, artifacts rejection, spatial smoothing and tensor estimation. Rigid registration was utilized to correct misalignments. Motion artifacts were rejected by using local Pearson correlation coefficient (LPCC). The performance of LPCC in characterizing relative differences between artifacts and artifact-free images was compared with that of the conventional correlation coefficient in 10 randomly selected DKI datasets. The influence of rejected artifacts with information of gradient directions and b values for the parameter estimation was investigated by using mean square error (MSE). The variance of noise was used as the criterion for MSEs. The clinical practicality of the proposed workflow was evaluated by the image quality and measurements in regions of interest on 36 DKI datasets, including 18 artifact-free (18 pediatric subjects) and 18 motion-corrupted datasets (15 pediatric subjects and 3 essential tremor patients).

Results

The relative difference between artifacts and artifact-free images calculated by LPCC was larger than that of the conventional correlation coefficient (p<0.05). It indicated that LPCC was more sensitive in detecting motion artifacts. MSEs of all derived parameters from the reserved data after the artifacts rejection were smaller than the variance of the noise. It suggested that influence of rejected artifacts was less than influence of noise on the precision of derived parameters. The proposed workflow improved the image quality and reduced the measurement biases significantly on motion-corrupted datasets (p<0.05).

Conclusion

The proposed post-processing workflow was reliable to improve the image quality and the measurement precision of the derived parameters on motion-corrupted DKI datasets. The workflow provided an effective post-processing method for clinical applications of DKI in subjects with involuntary movements.     

用氨基葡萄糖含量的测定值间接表示红曲菌固态发酵过程中生物量的研究

【目的】为准确快速地了解紫色红曲菌固态发酵中生物量的变化,【方法】采用理化方法测定菌体量和氨基葡萄糖含量,研究了不同培养时间、培养基组成、培养方式下菌体量与氨基葡萄糖含量的关系,建立生物量和氨基葡萄糖含量的换算关系式;构建关联该菌固态培养物近红外光谱数据与实测氨基葡萄糖含量的PLS模型。【结果】建立了可通过近红外光谱法测定氨基葡萄糖来快速预测固态发酵生物量的方法,其中最优近红外模型的校正集内部交叉验证均方根误差(RMSECV)为0.209 4,预测集相关系数(Rp)和均方根误差(RMSEP)分别为0.993 4和0.217 3;同时利用所建的换算关系式也大大提高了生物量计算的准确性。【结论】基于所建立的生物量和氨基葡萄糖的换算关系式,利用近红外光谱法可以快速并且较准确地测定紫色红曲菌固态发酵过程中生物量的变化。     

基于Renyi熵滤波的光声图像重建算法设计与实现

针对光声图像重建过程中存在的原始光声信号信噪比差、重建图像对比度低、分辨率不足等问题,提出了基于Renyi熵的光声图像重建滤波算法.该算法首先根据原始光声信号的Renyi熵分布情况,确定分割阈值,并滤除杂波信号;再利用滤波后的光声数据进行延时叠加光声图像重建.利用该滤波算法分别处理铅笔芯横截面(零维)、头发丝(一维)以及小鼠大脑皮层血管(二维)等不同维度样本的光声信号,实验结果表明:相比Renyi熵处理之前,重建图像对比度平均增强了32.45%,分辨率平均提高了30.78%,信噪比提高了47.66%,均方误差降低了35.01%;相比典型的滤波处理算法(模极大值法和阈值去噪法),本研究中图像的对比度、分辨率和信噪比分别提高了25.94%/10.60%、27.90%/19.48%、35.21%/10.60%,均方误差减小了28.57%/16.66%.因此,选择利用Renyi熵滤波算法处理光声信号,从而使光声图像重建质量得到大幅改善.