Genetic diagnosis on one case of primary pigmented nodular adrenal disease / 中华内分泌代谢杂志

Primary pigmented nodular adrenal disease (PPNAD) is a kind of autosomal dominant inherited disease. Patient in the study presented with Cushing's syndrome, and clinical and pathological diagnosis of PPNAD was confirmed. It is now confirmed that there are two relevant genes and their mutations may lead to PPNAD. This study showed no mutations in the patient, surpecting if there would be an alternative mechanism or a new gene in playing the role.

Method of automatic detection of brain lesion based on wavelet feature vector / 生物医学工程学杂志

A new method of automatic detection of brain lesion based on wavelet feature vector of CT images has been proposed in the present paper. Firstly, we created training samples by manually segmenting normal CT images into gray matter, white matter and cerebrospinal fluid sub images. Then, we obtained the cluster centers using FCM clustering algorithm. When detecting lesions, the CT images to be detected was automatically segmented into sub images, with a certain degree of over-segmenting allowed under the premise of ensuring accuracy as much as possible. Then we extended these sub images and extracted the features to compute the distances with the cluster centers and to determine whether they belonged to the three kinds of normal samples, or, otherwise, belonged to lesions. The proposed method was verified by experiments.

Study on Grey model of electroencephalogram and features of driving fatigue / 生物医学工程学杂志

Grey system theory was applied in analysis of Electroencephalogram (EEG) to extract features of driving fatigue in this study. Model GM(1,1) was built for EEG collected during simulative driving experiments. At the same time, the data of steering wheel movements and subjective fatigue level were analyzed as reference. The results of experiments reveal that the co-deviation of Model GM(1,1) parameter a and b, cov(a,b), coincides with the standard deviation of steering wheel movements. This indicates that Grey system theory is effective for EEG analysis and the parameters of GM(1,1) can well reflect the change of driving fatigue.

Detrended fluctuation analysis of physiological parameters during sleep / 生物医学工程学杂志

Detrended fluctuation analysis (DFA) is fit for studies on the long-range exponential correlations of non-stationary time serial. In this paper, for elucidating the characteristics of different sleep stages, DFA is adopted to analyze the physiological data collected during sleep. The parameters such as electroencephalogram (EEG), R-R interval sequence and stroke volume (SV) are analyzed, and the scaling exponent a is calculated. The experimental results reveal that the values of a differ much in different sleep stages,that the rules of EEG and SV are alike, that alpha increases with the deepening of sleep, but in inverse for R-R interval sequence that alpha decreases with the deepening of sleep. These indicate that the method of DFA is practical in the analysis of physiological parameters.

A novel segment-training algorithm for transmembrane helices prediction / 生物医学工程学杂志

This paper is devoted to predicting the transmembrane helices in proteins by statistical modeling. A novel segment-training algorithm for Hidden Markov modeling based on the biological characters of transmembrane proteins has been introduced into training and predicting the topological characters of transmembrane helices such as location and orientation. Compared to the standard Balm-Welch training algorithm, this algorithm has lower complexity while prediction performance is better than or at least comparable to other existing methods. With a 10-fold cross-validation test on a database containing 160 transmembrane proteins, an HMM model trained with this algorithm outperformed two other prediction methods: TMHMM and MEMSTAT; the novel method was validated by its prediction sensitivity (97.0%) and correct location (91.3%). The results showed that this algorithm is an efficient and a reasonable supplement to modeling and prediction of transmembrane helices.

Implementation of sector imaging mode with high signal-to-noise ratio in the high frame rate ultrasonic imaging system / 生物医学工程学杂志

The high frame rate (HFR) ultrasonic imaging system, which is developed with limited diffraction beams, constructs images at a high frame rate. However the rectangular imaging area, to some extent, restricts the far field imaging information. At the same time, because of one transmission for constructing image, the system suffers from low SNR. In this paper we present a computationally efficient method to construct sector mode image and to increase the SNR in HFR system. The method uses Golay complementary sequence as excitation to realize two transmission events. Each event simultaneously transmits two plane waves with different transmission angle. Then the received echo signals related to different angle are separated according to orthogonality of Golay complementary sequence and used to construct two images of different area by HFR method. Finally the two images are synthesized to one frame of sector mode image.

Quasi-Newton iteration algorithm for ICA and its application in VEP feature extraction / 生物医学工程学杂志

Some noises still exist in the single-trial averaged visual evoked potentials (VEP), so further extraction of the above results is of significance. Independent component analysis (ICA)can separate the sources from their mixtures and make the output statistically as independent as possible; it can remove noises effectively. In this paper, the principle, experiment analyses and results of ICA based on quasi-Newton iteration rule for VEP feature extraction are introduced, It is compared with the fixed-point FastICA algorithm. The experiment results show that the provided algorithm may reinforce signals effectively and extract distinct P300 from the single-trial averaged VEP. It is of good applicability.

Nonlinear analysis of multi-channel EEG and its application to mental workload detection / 生物医学工程学杂志

Mental workload research is important to people's health and work efficiency, Psychophysiological measures such as electroencephalography (EEG), ECG and respiration measures can be used to predict mental workload level. A Multi-channel phase-space reconstruction method is proposed in this paper which rearranges signal serials by the correlation coefficients and select time delay by signal determinism. The study of determinism and correlation dimension on simulative data exhibits a good performance. The result of EEG series shows a clearly consistency to workload level variety. The method is useful for multi-channel signals nonlinear analysis and mental workload detection.

Prediction of protein solvent accessibility with Markov chain model / 生物医学工程学杂志

Residues in protein sequences can be classified into two (exposed / buried) or three (exposed/intermediate/buried) states according to their relative solvent accessibility. Markov chain model (MCM) had been adopted for statistical modeling and prediction. Different orders of MCM and classification thresholds were explored to find the best parameters. Prediction results for two different data sets and different cut-off thresholds were evaluated and compared with some existing methods, such as neural network, information theory and support vector machine. The best prediction accuracies achieved by the MCM method were 78.9% for the two-state prediction problem and 67.7% for the three-state prediction problem, respectively. A comprehensive comparison for all these results shows that the prediction accuracy and the correlative coefficient of the MCM method are better than or comparable to those obtained by the other prediction methods. At the same time, the advantage of this method is the lower computation complexity and better time-consuming performance.

Intra-subject Image Registration between Expiration and Inspiration Lung Volumes of High Resolution CT / 航天医学与医学工程

Objective To register two breath-hold lung volumes image from one subject with deep expiration and deep inspiration.Methods Three pairs of thoracic high resolution CT serial from three subjects were collected under two breath-hold respiration stages.The lung parenchyma of every serial was segmented using the serial segmentation algorithm.Left and right lungs were stored separately.Expiration and inspiration volume images of single lung were registered.Firstly,affine transformation parameters were found based on the anatomic flag surfaces and expiration image volume was re-sampled with affine transformation.Secondly,"Demons" algorithm was employed to register two image volumes non-rigidly.Results Two lung surfaces and the inner structures have a nice registration.The average volume overlap of two images before registration is 0.7982.After global affine transformation,it improves to 0.8936.After "Demons",it is up to 0.9544.The average descending percentage of root mean square errors is 19.83%(after the global affine transformation) and 49.43%(after the "Demons" non-rigid registration).Conclusion The intra-subject registration between two lung image volumes with large deformations described here has an effective registration result.It offers a good base to analyze the lung respiration function.

3D Reconstruction of High-resolution Volume Data Based on Surface Points / 航天医学与医学工程

Objective: To develop a way of high-quality real-time three dimension surface reconstruction for high-resolution volume data.Method 3D surface point sets of single organ were using a method of binding the threshold and morphological operations.The normal vector of every surface point was calculated.According to the gray gradients of volume data,the triangle face was replaced by surface points to describe the organ surface,and the surface was displayed with OpenGL interface of display card after defining the color and transparent of the organ surface.Result Based on hardware platform of personal computer,the reconstruction of skeleton and skin for the digitized virtual Chinese man No.1(VCH-M1) from CT database was constructed,the rendering speed was faster than 25 F/s.Conclusion The algorithm is capable of realizing a real-time rendering for 512?512?1720 high resolution volume data.

Off-line experiments and analysis of independent brain--computer interface / 生物医学工程学杂志

In order to study event-related desynchronization (ERD) related to voluntary movement, we designed two experiments. In the first experiment, untrained subjects were required to imagine the action of typing with left or right index finger for about 1 second before real action, whereas they were required to type instantly after instruction in the second experiment. By analyzing spontaneous EEG signals between the instruction and the action, we predicted which finger was used. The prediction accuracy in the first experiment fell from 85% to 71% with the progress of experiment, the average accuracy being 78%, whereas the prediction result was almost random guess in the second experiment. The results demonstrate that (1) ERD patterns are significantly affected by the effective duration of motion imagination, (2) unconscious reduction of this duration can decrease the prediction accuracy. Therefore, when designing subsequent BCI experiments, we should devote our attention to the question of how to keep the effective duration of motion imagination.

Application of high frequency component in classification of different mental tasks / 生物医学工程学杂志

Electroencephalogram (EEG) signals of different mental tasks were preprocessed using Independent Component Analysis (ICA). Auto-Regressive (AR) model was used to extract the feature, and Back-Propagation (BP) network as the classifier. When features were extracted from 20-100 Hz high frequency range, the classification accuracy was the same as that taken from the whole frequency range and was more higher than the result of 2-35 Hz normal EEG rhythm. The explanation of this phenomenon is: brain displays different rhythm assimilation during different mental task under the effect of 60 Hz power frequency, so the high frequency components of EEG include more mental modulated information which is useful for improving the classification accuracy. The result presents a new evidence for the brain rhythm assimilation phenomenon and gives a novel feature extraction method for realizing high accuracy real-time BCI based on mental task.

Fast extraction of iso-surface in surface rendering of medical images / 生物医学工程学杂志

In this paper a new direct volume rendering method is presented for fast extraction of iso-surface by adopting the idea from the Shear-Warp algorithm. By creating the sorted volumetric data from the original volume data and specifying a value range of data which determines the part of the sorted volumetric data traversed, the amount of volume data traversed would be reduced obviously and the extraction operation of iso-surface would be very fast. In addition, we can adjust the value range to obtain the different rendering speed and image quality according to the purpose in application. Moreover, the proposed algorithm will not output any intermediate data after the sorted volumetric data being produced. Therefore, it is possible to realize the rapid 3D surface reconstruction for medical images on the personal computer without the support of any hardware accelerator.

Analyzing sleep EEG using correlation dimension and approximate entropy / 生物医学工程学杂志

Correct sleep scoring is the base of sleep studying; nonlinear features of EEG can represent different sleep stages. In this paper, correlation dimension (D2) and approximate entropy (ApEn) of sleep EEG have been calculated. The statistical results reveal that: D2 does not come to be saturated when the embedding dimension increases, but the relative value of D2 can effectively distinguish different sleep stages. ApEn has the advantage of calculating simply, steady result and representing preferably different sleep stages. ApEn and the relative value of D2 reveal, from different point of view, the same rule about EEG (brain) complexity changing, that is, both complexity and its fluctuation are maximal in the subject's awake hour, are decreasing with the deepening of sleep, but the complexity in REM is about the level between S1 and S2.

Autoregressive model order property for sleep EEG / 生物医学工程学杂志

Traditional sleep scoring system describes the sleep EEG characterized by features in time domain as well as frequency domain. Power Spectral Density (PSD) is one of the well-used methods to observe the occurrence of specified rhythms. However, the parameter model based PSD estimation is used with the assumption that the model order is determined as low as possible through prior knowledge. This paper briefs the development of Autoregressive Model Order (ARMO) criterion, and provides the distribution of ARMOs for specified sleep EEG, which shows that ARMOs concentrate on several well separated regions that are indicative of the microstructure and transition states. This study suggests the promising perspective of ARMO as a special EEG feature for weighing complexity, randomness and rhythm components.

Computer simulation of high frame rate ultrasonic imaging system based on the angular spectrum concept / 生物医学工程学杂志

A high frame rate (HFR) ultrasonic imaging method developed by Jianyu Lu has been attracting attention in the related imaging area. Because a special weighting on the received signal is needed to implement this method, the imaging system is complicated. This paper presents a new kind of theroetical analysis for the HFR imaging system in view of the angular spectrum concept. Based on the study, the special weighting process can be replaced by Fourier transform. Computer simulation demonstrates the correctness of the analysis. It shows that the constructed images by the new method have the same high quality as those obtained by using the original HFR method while the system implementation is greatly simplified.

Detection of abnormalities in digital mammograms based on Support Vector Machines / 医疗卫生装备

Objective To search an approach based on Support Vector Machine (SVM) for detection of different abnormalities including micro-calcifications and masses from digital mammograms. Methods Such detections were formulated as supervised-learning problems and SVM was applied to the detection algorithm. After the regions of interest were pre-processed by specific rectangular windows, three kinds of parameters were extracted, including the direct pixel value parameter, the parameters from Spatial Grey Level Dependency (SGLD) matrices and from Discrete Cosine Transform (DCT). At first, each kind of parameter was taken as the input of SVM to train and test the machine respectively. Then all the parameters were incorporated into the input of SVM. Results the classification accuracy is 92.28%, 90.35% and 91.12% respectively when only one parameter input. The classification accuracy reaches 99.23% when all the parameter incorporated. Conclusion The parameters extracted from the regions of interest in digital mammograms can reflect the characteristics of different regions and SVM is a powerful tool for the detection of abnormalities from digital mammograms.

Application of complexity sequence in sleep staging based on sleep EEG data / 生物医学工程学杂志

In this paper an approach of time-window complexity sequence is applied to sleep EEG analysis. This approach can reduce the loss of state information due to the nonstationarity of EEG signal and the unevenness of state space, and can overcome certain limitations of the complexity itself to some extent. It will help to extract the state features of EEG in different sleep stages. In addition, we preprocess EEG by adopting ICA and wavelet transform (WT). The results show that some physiological artifact in EEG can be eliminated effectively by these methods, and the sleep staging based on sleep EEG data will be more exact.

Improvement on simulation algorithm of excitation propagation in heart modeling / 生物医学工程学杂志

It is important to simulate the excitation propagation process of cardiac bio-electricity in the research of ECG forward problem. Traditional methods describe them with wave simulation algorithm such as LFX simulation algorithm and vector propagation algorithm etc, these methods have some problems to certain extent, due to the presence of discreteness of space and time and asymmetry of the myocardium. This paper discussed the simulation algorithm in 2-dimension space under the circumstance of layered and non-layered structure of myocardium. By calculating the theoretic values of simulating time based on Huygen's principle, we found that there were errors in LFX algorithm and no errors in vector propagation algorithm under the circumstance of non-layered structure of the myocardium, no mater what myocardium is isotropic or anisotropic. However, there exist errors from both algorithms when the myocardium has the layered structure. An improved algorithm is proposed and the simulations have been performed to examine the efficacy of the new algorithm, and the errors are reduced obviously. By increasing the number of myocardial blocks in the model, we also analyzed its influence on the error of simulation algorithm.