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Abstract Background In this paper a novel method for prostate segmentation in transrectal ultrasound images is presented. Methods A segmentation procedure consisting of four main stages is proposed. In the first stage, a locally adaptive contrast enhancement method is used to generate a well-contrasted image. In the second stage, this enhanced image is thresholded to extract an area containing the prostate (or large portions of it). Morphological operators are then applied to obtain a point inside of this area. Afterwards, a Kalman estimator is employed to distinguish the boundary from irrelevant parts (usually caused by shadow) and generate a coarsely segmented version of the prostate. In the third stage, dilation and erosion operators are applied to extract outer and inner boundaries from the coarsely estimated version. Consequently, fuzzy membership functions describing regional and gray-level information are employed to selectively enhance the contrast within the prostate region. In the last stage, the prostate boundary is extracted using strong edges obtained from selectively enhanced image and information from the vicinity of the coarse estimation. Results A total average similarity of 98.76%(± 0.68) with gold standards was achieved. Conclusion The proposed approach represents a robust and accurate approach to prostate segmentation.

There has been a growing interest in image fusion technologies, but how to objectively evaluate the quality of fused images has not been fully understood. Here, we propose a method for objective quality assessment of multiexposure multifocus image fusion based on the evaluation of three key factors of fused image quality: 1) contrast preservation; 2) sharpness; and 3) structure preservation. Subjective experiments are conducted to create an image fusion database, based on which, performance evaluation shows that the proposed fusion quality index correlates well with subjective scores, and gives a significant improvement over the existing fusion quality measures. [ABSTRACT FROM AUTHOR]

This paper presents an adaptive grid-voltage sensor- less control scheme for inverter-based distributed generation units based on an adaptive grid-interfacing model. An adaptive grid- interfacing model is proposed to estimate, in real time, the inter- facing parameters seen by the inverter and the grid-voltage vector simultaneously. A reliable solution to the present nonlinear estimation problem is presented by combining a grid-voltage estimator with an interfacing parameter estimator in a parallel structure. Both estimators adjust the grid-interfacing model in a manner that minimizes the current error between the grid model and the actual current dynamics, which acts as a reference model. The estimated quantities are utilized within the inner high-bandwidth current control loop and the outer power controller to realize an adaptive grid-voltage sensorless interfacing scheme. Theoretical analysis and simulation results are provided to demonstrate the validity and usefulness of the proposed interfacing scheme. [ABSTRACT FROM AUTHOR]

This paper focuses on extracting and analyzing different spectral features from transrectal ultrasound (TRUS) images for prostate cancer recognition. First, the information about the images' frequency domain features and spatial domain features are combined using a Gabor filter and then integrated with the expert radiologist's information to identify the highly suspicious regions of interest (ROIs). The next stage of the proposed algorithm is to scan each identified region in order to generate the corresponding 1-D signal that represents each region. For each ROI, possible spectral feature sets are constructed using different new geometrical features extracted from the power spectrum density (PSD) of each region's signal. Next, a classifier-based algorithm for feature selection using particle swarm optimization (PSO) is adopted and used to select the optimal feature subset from the constructed feature sets. A new spectral feature set for the TRUS images using estimation of signal parameters via rotational invariance technique (ESPRIT) is also constructed, and its ability to represent tissue texture is compared to the PSD-based spectral feature sets using the support vector machines (SVMs) classifier. The accuracy obtained ranges from 72.2% to 94.4%, with the best accuracy achieved by the ESPRIT feature set. [ABSTRACT FROM AUTHOR]

In this paper, a novel algorithm, based on calculating the energy operator of a sinusoidal waveform to track the voltage flicker, is presented. The mathematical derivation of the proposed algorithm different circuit designs required to realize it are described. The proposed algorithm is fast and robust and requires only a few samples to calculate the energy. The simulation and the experimental results prove that the new algorithm can successfully track the envelope. There are no spikes in the envelope even when the voltage signal is suddenly changed at its peak value. [ABSTRACT FROM AUTHOR]

Distributed measurement architecture, due to its efficiency, is used to monitor the power quality in the electric systems. This paper introduces a novel algorithm to determine the optimum allocations of power quality monitors to reduce the cost of the distributed monitoring system taking into account the data redundancy. The optimization problem is formulated as a covering and packing one which can be manipulated by integer linear programm algorithms. The appropriate constraints are deduced by the electrical circuit topology independent of the load parameters. In addition, the problem is adopted to a general form which can be implemented by any optimization package. The proposed algorithm is applied to five different systems for validation. Then, the results are discussed in terms of the cost and data redundancy. [ABSTRACT FROM AUTHOR]

This paper introduces a novel method for the mitigation of the voltage sag and voltage flicker by using Kalman filter and its derivatives (adaptive, and extended). The Kalman filter is used as a tool to extract both the instantaneous envelope of the voltage sags, and to extract the Instantaneous Flicker Level (IFL) of the voltage flicker. Also, this paper demonstrates the advantages of using the Kalman filter instead of the existing tools for tracking and extracting voltage disturbances. Digital simulation results are presented to illustrate the mitigation of unbalanced voltage sags, and the compensation of the cyclic and noncyclic voltage flicker by employing the proposed algorithm. [ABSTRACT FROM PUBLISHER]

Distributed Generation (DG) is used widely in the modern distribution systems. This paper proposes a novel functionality of the interface between DG and the utility network to mitigate the voltage flicker and to regulate the voltage at the Point of Common Coupling (PCC) in addition to its main function of controlling the power flow. A new control algorithm for the DG interface based on the Hilbert transform (HT) is presented. The HT is employed as an effective technique for tracking the voltage flicker levels in distribution systems. The mathematical simplicity of the proposed technique, compared with the commonly used algorithms in the literature, renders them competitive candidates for the on-line tracking of voltage flicker. The accurate tracking of the HT facilitates its implementation for the control of flicker mitigation devices. Simulation results are provided to verify the tracking capabilities of the HT and to evaluate the performance of the proposed DG interface for multifunction operation. [ABSTRACT FROM PUBLISHER]

This paper presents a generalized control algorithm for voltage disturbance extraction and mitigation. The proposed mitigating device is the dynamic voltage restorer (DVR). A DVR is commonly used to mitigate the voltage sags. In this paper the proposed DVR can compensate the voltage unbalance and mitigate voltage harmonics in the time of normal operation as well as performs its basic function during the fault condition. The suggested control algorithm employs an adaptive perceptron to effectively and adaptively track and extract the most common voltage harmonics, voltage unbalance (which include negative and zero sequence voltage drops), and different types of voltage sags, which include balanced and unbalanced voltage sags. Digital simulation results are obtained using PSCADIEMTDC to verify the effectiveness of the proposed control algorithm. Experimental results are demonstrated to prove the practicality of the mitigating device. [ABSTRACT FROM AUTHOR]

Envelope tracking has many important applications in electrical distribution systems for either flicker meters or flicker compensators. This paper presents a novel control technique for flicker mitigation. This technique is based on the instantaneous tracking of the measured voltage envelope. The ADAptive LINEar neuron (ADALINE) algorithm, and the Recursive Least Square (RLS) algorithm are introduced for the flicker envelope tracking. The ADALINE algorithm is characterized by a light computational demand, unlike that of existing techniques; the RLS algorithm outperforms the ADALINE algorithm by its fast con- vergence and robust tracking performance. Both the ADALINE and the RLS algorithms give accurate results even under rapid dynamic changes. The paper investigates the effects of different parameters on the performance of the ADALINE algorithm and that of the RLS algorithm. Extensive simulations of the proposed flicker tracking algorithms are conducted to evaluate their performance for the tracking and mitigation of voltage flicker. The ADALINE and the RLS algorithms are examined by tracking and mitigating the flicker produced by a resistance welder and an arc furnace in a simple distribution system simulated in the PSCAD/EMTDC package. [ABSTRACT FROM AUTHOR]

Distributed Generation (DG) exists in distribution systems and is installed by either the utility or the customers. This paper proposes a novel utilization of the existing DG nonlinear interface not only to control the active power flow, but also to mitigate unbalance and harmonics, and to manage the reactive power of the system. The proposed Flexible Distributed Generation (FDG) is similar in functionality to FACTS, but works at the distribution level. Moreover, a novel ADAptive LINEar neuron (ADALINE) structure is presented. The new structure is applied to multi output (MO) systems for parameter tracking/estimation, and is called MO-ADALINE. It is dedicated to symmetrical components estimation. The control loop combines a Fuzzy Logic Controller (FLC) for voltage regulation, and a processing unit-based ADALINE to deal with unbalance, harmonics and reactive power compensation. One advantage of the proposed control system is its insensitivity to parameter variation, a necessity for distribution system applications. Simulations of the suggested FDG based control algorithm are conducted to evaluate the performance of the novel system. [ABSTRACT FROM AUTHOR]

Symmetrical components as well as harmonic tracking are of great importance in many applications in power systems such as power quality and protection. This paper introduces a novel Adaptive linear combiner (ADALINE) structure for symmetrical components estimation. This structure is capable of dealing with multi-output systems for parameter tracking/estimation rather than the existing ADALINE, which deals only with single output systems. As the new topology deals with Multi-Output systems, it is called MO-ADALINE. Moreover, the paper presents a new processing unit, which can estimate sym- metrical and harmonic components from the measured current signals. The advantages of this proposed unit are its independence of the voltage waveform and its ability to give information about the reactive component of the resolved current Simulation results are given to validate the proposed algorithms. [ABSTRACT FROM AUTHOR]

Sharpness is an important determinant in visual assessment of image quality. The human visual system is able to effortlessly detect blur and evaluate sharpness of visual images, but the underlying mechanism is not fully understood. Existing blur/sharpness evaluation algorithms are mostly based on edge width, local gradient, or energy reduction of global/local high frequency content. Here we understand the subject from a different perspective, where sharpness is identified as strong local phase coherence (LPC) near distinctive image features evaluated in the complex wavelet transform domain. Previous LPC computation is restricted to be applied to complex coefficients spread in three consecutive dyadic scales in the scale-space. Here we propose a flexible framework that allows for LPC computation in arbitrary fractional scales. We then develop a new sharpness assessment algorithm without referencing the original image. We use four subject-rated publicly available image databases to test the proposed algorithm, which demonstrates competitive performance when compared with state-of-the-art algorithms.

Background: Among different medical image modalities, ultrasound imaging has a very widespread clinical use. But, due to some factors, such as poor image contrast, noise and missing or diffuse boundaries, the ultrasound images are inherently difficult to segment. An important application is estimation of the location and volume of the prostate in transrectal ultrasound (TRUS) images. For this purpose, manual segmentation is a tedious and time consuming procedure., Methods: We introduce a new method for the segmentation of the prostate in transrectal ultrasound images, using a reinforcement learning scheme. This algorithm is used to find the appropriate local values for sub-images and to extract the prostate. It contains an offline stage, where the reinforcement learning agent uses some images and manually segmented versions of these images to learn from. The reinforcement agent is provided with reward/punishment, determined objectively to explore/exploit the solution space. After this stage, the agent has acquired knowledge stored in the Q-matrix. The agent can then use this knowledge for new input images to extract a coarse version of the prostate., Results: We have carried out experiments to segment TRUS images. The results demonstrate the potential of this approach in the field of medical image segmentation., Conclusion: By using the proposed method, we can find the appropriate local values and segment the prostate. This approach can be used for segmentation tasks containing one object of interest. To improve this prototype, more investigations are needed.

Background: Identifying the location and the volume of the prostate is important for ultrasound-guided prostate brachytherapy. Prostate volume is also important for prostate cancer diagnosis. Manual outlining of the prostate border is able to determine the prostate volume accurately, however, it is time consuming and tedious. Therefore, a number of investigations have been devoted to designing algorithms that are suitable for segmenting the prostate boundary in ultrasound images. The most popular method is the deformable model (snakes), a method that involves designing an energy function and then optimizing this function. The snakes algorithm usually requires either an initial contour or some points on the prostate boundary to be estimated close enough to the original boundary which is considered a drawback to this powerful method., Methods: The proposed spectral clustering segmentation algorithm is built on a totally different foundation that doesn't involve any function design or optimization. It also doesn't need any contour or any points on the boundary to be estimated. The proposed algorithm depends mainly on graph theory techniques., Results: Spectral clustering is used in this paper for both prostate gland segmentation from the background and internal gland segmentation. The obtained segmented images were compared to the expert radiologist segmented images. The proposed algorithm obtained excellent gland segmentation results with 93% average overlap areas. It is also able to internally segment the gland where the segmentation showed consistency with the cancerous regions identified by the expert radiologist., Conclusion: The proposed spectral clustering segmentation algorithm obtained fast excellent estimates that can give rough prostate volume and location as well as internal gland segmentation without any user interaction.