There are several approaches for Radio Resource Management (RRM) in multicarrier cellular systems. This work analyzes and compares two of them: rate-adaptive resource allocation (sub-carriers and power) based on instantaneous data rates, and utility-based packet scheduling based on average data rates. A fundamental RRM problem in wireless cellular networks was chosen as a background to evaluate the aforementioned approaches: the trade-off between system spectral efficiency and fairness among the users when opportunistic allocation is used. Extensive system-level simulations were performed and important network metrics such as total cell throughput, mean user throughput, system fairness index and user satisfaction were assessed. It was concluded from the simulation results that it is possible to achieve an efficient trade-off between resource efficiency and fairness using any of the two RRM approaches. However, utility-based packet scheduling algorithms based on average data rates have the advantage of presenting higher user satisfaction with less computational complexity.
{"title":"Rate Adaptive Resource Allocation and Utility-Based Packet Scheduling in Multicarrier Systems","authors":"E. Rodrigues, F. Casadevall","doi":"10.1234/MJEE.V5I1.371","DOIUrl":"https://doi.org/10.1234/MJEE.V5I1.371","url":null,"abstract":"There are several approaches for Radio Resource Management (RRM) in multicarrier cellular systems. This work analyzes and compares two of them: rate-adaptive resource allocation (sub-carriers and power) based on instantaneous data rates, and utility-based packet scheduling based on average data rates. A fundamental RRM problem in wireless cellular networks was chosen as a background to evaluate the aforementioned approaches: the trade-off between system spectral efficiency and fairness among the users when opportunistic allocation is used. Extensive system-level simulations were performed and important network metrics such as total cell throughput, mean user throughput, system fairness index and user satisfaction were assessed. It was concluded from the simulation results that it is possible to achieve an efficient trade-off between resource efficiency and fairness using any of the two RRM approaches. However, utility-based packet scheduling algorithms based on average data rates have the advantage of presenting higher user satisfaction with less computational complexity.","PeriodicalId":37804,"journal":{"name":"Majlesi Journal of Electrical Engineering","volume":"5 1","pages":"38-49"},"PeriodicalIF":0.0,"publicationDate":"2011-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66017718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chen Xiang, Zhao Ming, Zhao Juntao, C. Jianwen, Wang Jing
Wireless baseband processing, which is characterized by high computational complexity and high data throughput, is regarded as the most challenging issue for software radio (SR) systems, especially for the General Purpose Processor (GPP)-based SR systems. To overcome this implementation difficulty in SR systems, the multicore architecture has been proposed as the GPP-based SR platform, for example, multicore Central Processing Unit (CPU), Graphic Processing Unit (GPU) and Cell processors. In this paper, the Cell processor is considered as the core component in the GPP-based SR platform, and the channel decoding modules for convolutional, Turbo and Low-density parity-check (LDPC) codes of WiMAX systems are investigated and efficiently implemented on Cell processor. With a single Synergistic Processor Element (SPE) running at 3.2GHz, the implemented channel decoders can throughput up to 30Mbps, 1.36Mbps and 1.71Mbps for the above three codes, respectively. Moreover, the decoding modules can be easily integrated to the SR system and can provide a highly integrated SR solution.
{"title":"High Performance Channel Decoders on CELL Broadband Engine for WiMAX System","authors":"Chen Xiang, Zhao Ming, Zhao Juntao, C. Jianwen, Wang Jing","doi":"10.1234/MJEE.V5I1.377","DOIUrl":"https://doi.org/10.1234/MJEE.V5I1.377","url":null,"abstract":"Wireless baseband processing, which is characterized by high computational complexity and high data throughput, is regarded as the most challenging issue for software radio (SR) systems, especially for the General Purpose Processor (GPP)-based SR systems. To overcome this implementation difficulty in SR systems, the multicore architecture has been proposed as the GPP-based SR platform, for example, multicore Central Processing Unit (CPU), Graphic Processing Unit (GPU) and Cell processors. In this paper, the Cell processor is considered as the core component in the GPP-based SR platform, and the channel decoding modules for convolutional, Turbo and Low-density parity-check (LDPC) codes of WiMAX systems are investigated and efficiently implemented on Cell processor. With a single Synergistic Processor Element (SPE) running at 3.2GHz, the implemented channel decoders can throughput up to 30Mbps, 1.36Mbps and 1.71Mbps for the above three codes, respectively. Moreover, the decoding modules can be easily integrated to the SR system and can provide a highly integrated SR solution.","PeriodicalId":37804,"journal":{"name":"Majlesi Journal of Electrical Engineering","volume":"5 1","pages":"21-31"},"PeriodicalIF":0.0,"publicationDate":"2011-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66017695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. M. Ferrández, Victor Lorente, J. Garrigós, Eduardo Fernández
The main objective of this work is to analyze the computing capabilities of human neuroblastoma cultured cells and to define stimulation patterns able to modulate the neural activity in response to an image for controlling an autonomous robot. Multielectrode Arrays Setups have been designed for direct culturing neural cells over silicon or glass substrates, providing the capability to stimulate and record simultaneously populations of neural cells. If we are able to modify the selective responses of some cells with an external pattern stimuli over different time scales, the neuroblastoma-cultured structure could be trained to process image sequences.
{"title":"Image Coding for Robotic Guidance Using Neuroblastoma Cultures","authors":"J. M. Ferrández, Victor Lorente, J. Garrigós, Eduardo Fernández","doi":"10.1234/MJEE.V5I1.380","DOIUrl":"https://doi.org/10.1234/MJEE.V5I1.380","url":null,"abstract":"The main objective of this work is to analyze the computing capabilities of human neuroblastoma cultured cells and to define stimulation patterns able to modulate the neural activity in response to an image for controlling an autonomous robot. Multielectrode Arrays Setups have been designed for direct culturing neural cells over silicon or glass substrates, providing the capability to stimulate and record simultaneously populations of neural cells. If we are able to modify the selective responses of some cells with an external pattern stimuli over different time scales, the neuroblastoma-cultured structure could be trained to process image sequences.","PeriodicalId":37804,"journal":{"name":"Majlesi Journal of Electrical Engineering","volume":"5 1","pages":"12-20"},"PeriodicalIF":0.0,"publicationDate":"2011-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66017468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The number of attacks in computer networks has grown extensively, and many new intrusive methods have appeared. Intrusion detection is known as an effective method to secure the information and communication systems. In this paper, the performance of Elman and partial-connected dynamic neural network (PCDNN) architectures are investigated for misuse detection in computer networks. To select the most significant features, logistic regression is also used to rank the input features of mentioned neural networks (NNs) based on the Chi-square values for different selected subsets in this work. In addition, genetic algorithm (GA) is used as an optimization search scheme to determine the sub-optimal architecture of investigated NNs with selected input features. International knowledge discovery and data mining group (KDD) dataset is used for training and test of the mentioned models in this study. The features of KDD data are categorized as basic, content, time-based traffic, and host-based traffic features. Empirical results show that PCDNN with selected input features and categorized input connections offers better detection rate (DR) among the investigated models. The mentioned NN also performs better in terms of cost per example (CPE) when compared to other proposed models in this study. False alarm rate (FAR) of the PCDNN with selected input features and categorized input connections is better than other proposed models, as well. Normal 0 false false false EN-US X-NONE AR-SA MicrosoftInternetExplorer4
{"title":"Application of Partial-Connected Dynamic and GA-Optimized Neural Networks to Misuse Detection Using Categorized and Ranked Input Features","authors":"M. Sheikhan, Z. Jadidi, A. Farrokhi","doi":"10.1234/MJEE.V5I1.350","DOIUrl":"https://doi.org/10.1234/MJEE.V5I1.350","url":null,"abstract":"The number of attacks in computer networks has grown extensively, and many new intrusive methods have appeared. Intrusion detection is known as an effective method to secure the information and communication systems. In this paper, the performance of Elman and partial-connected dynamic neural network (PCDNN) architectures are investigated for misuse detection in computer networks. To select the most significant features, logistic regression is also used to rank the input features of mentioned neural networks (NNs) based on the Chi-square values for different selected subsets in this work. In addition, genetic algorithm (GA) is used as an optimization search scheme to determine the sub-optimal architecture of investigated NNs with selected input features. International knowledge discovery and data mining group (KDD) dataset is used for training and test of the mentioned models in this study. The features of KDD data are categorized as basic, content, time-based traffic, and host-based traffic features. Empirical results show that PCDNN with selected input features and categorized input connections offers better detection rate (DR) among the investigated models. The mentioned NN also performs better in terms of cost per example (CPE) when compared to other proposed models in this study. False alarm rate (FAR) of the PCDNN with selected input features and categorized input connections is better than other proposed models, as well. Normal 0 false false false EN-US X-NONE AR-SA MicrosoftInternetExplorer4","PeriodicalId":37804,"journal":{"name":"Majlesi Journal of Electrical Engineering","volume":"5 1","pages":"1-11"},"PeriodicalIF":0.0,"publicationDate":"2011-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66017417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents the comparative performance of neuro- Fuzzy controlled Voltage Source Converters (VSC) based Flexible AC Transmission System (FACTS) devices, such as Static Synchronous Series Compensator (SSSC), Static Synchronous Compensator (STATCOM), and Unified Power Flow Controller (UPFC) in terms of improvement in transient stability. In neuro-fuzzy control method the simplicity of fuzzy systems and the ability of training in neural networks have been combined. The training data set the parameters of membership functions in fuzzy controller. This Adaptive Network Fuzzy Inference System (ANFIS) can track the given input-output data in order to conform to the desired controller. The maximization of energy function of UPFC is used as an objective function to generate the training data. Proposed method is tested on a single machine infinitive bus system to confirm its performance through simulation. The results prove the noticeable influence of ANFIS controlled UPFC on increasing Critical Clearing Time (CCT) of system.
{"title":"COMPARISON OF ANFIS BASED SSSC, STATCOM AND UPFC CONTROLLERS FOR TRANSIENT STABILITY IMPROVEMENT","authors":"A. Shishebori, F. Taki, S. Abazari, G. Markadeh","doi":"10.1234/MJEE.V4I4.422","DOIUrl":"https://doi.org/10.1234/MJEE.V4I4.422","url":null,"abstract":"This paper presents the comparative performance of neuro- Fuzzy controlled Voltage Source Converters (VSC) based Flexible AC Transmission System (FACTS) devices, such as Static Synchronous Series Compensator (SSSC), Static Synchronous Compensator (STATCOM), and Unified Power Flow Controller (UPFC) in terms of improvement in transient stability. In neuro-fuzzy control method the simplicity of fuzzy systems and the ability of training in neural networks have been combined. The training data set the parameters of membership functions in fuzzy controller. This Adaptive Network Fuzzy Inference System (ANFIS) can track the given input-output data in order to conform to the desired controller. The maximization of energy function of UPFC is used as an objective function to generate the training data. Proposed method is tested on a single machine infinitive bus system to confirm its performance through simulation. The results prove the noticeable influence of ANFIS controlled UPFC on increasing Critical Clearing Time (CCT) of system.","PeriodicalId":37804,"journal":{"name":"Majlesi Journal of Electrical Engineering","volume":"4 1","pages":"48-54"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66017855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The direct force thrust control (DTFC) is linear type of the direct torque control (DTC) method. The advantages of DTFC method are structure simplicity, low dependency to motor parameters and no requirement to coordination transformations. In this paper this method is modified in order to eliminate the defects that include the switching frequency and exciting large ripples of force and flux. In previous works, the structure simplicity of DTC, rare calculations to reduce the force ripples and fixing switching frequency are disaffirmed. With regards to keeping DTC advantages, a new method is presented in this paper to eliminate the defects by the aid of neural network. Also, the precise non-linear behavior of PMLSM motor in DTC has been considered by using space vector modulation. Finally, the simulation results concluded by the submitted intelligent DTC-SVM method are more satisfactory than other methods.
{"title":"Forecasting PMLSM Direct Thrust Control Based on Neural Network by Considering Motors Dynamic Behavior and Speed Effects","authors":"Shahgholian Ghazanfar, A. D. Zadeh","doi":"10.1234/MJEE.V4I4.300","DOIUrl":"https://doi.org/10.1234/MJEE.V4I4.300","url":null,"abstract":"The direct force thrust control (DTFC) is linear type of the direct torque control (DTC) method. The advantages of DTFC method are structure simplicity, low dependency to motor parameters and no requirement to coordination transformations. In this paper this method is modified in order to eliminate the defects that include the switching frequency and exciting large ripples of force and flux. In previous works, the structure simplicity of DTC, rare calculations to reduce the force ripples and fixing switching frequency are disaffirmed. With regards to keeping DTC advantages, a new method is presented in this paper to eliminate the defects by the aid of neural network. Also, the precise non-linear behavior of PMLSM motor in DTC has been considered by using space vector modulation. Finally, the simulation results concluded by the submitted intelligent DTC-SVM method are more satisfactory than other methods.","PeriodicalId":37804,"journal":{"name":"Majlesi Journal of Electrical Engineering","volume":"4 1","pages":"35-41"},"PeriodicalIF":0.0,"publicationDate":"2010-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66017197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In a permanent magnet (PM) linear motor, there is a force ripple which is detrimental to positioning. This force ripple is mainly due to a cogging force and a mutual force ripple. These forces are affected by the geometric parameters of a brushless PM motor, such as the width of the magnet, the height of the magnet, the shifted length of the magnetic pole, the length and height of the armature and the slot width. The optimal design can be found by considering force ripple as a cost function and the geometric parameters as design variables. In this paper, we calculate the flux density distribution in the air gap using the analytic solution of Laplace and Possion equations in the function of geometric parameters. The cogging force is obtained by integrating the Maxwell stress tensor, which is described by the flux density distribution on the slot face and end face of the iron core of an armature. Finally, a finite element method is presented in order to compare with the previous method.
{"title":"Calculation of Cogging Force in Permanent Magnet Linear Motor Using Analytical and Finite Element Methods","authors":"M. Zare, M. Marzband","doi":"10.1234/MJEE.V4I4.310","DOIUrl":"https://doi.org/10.1234/MJEE.V4I4.310","url":null,"abstract":"In a permanent magnet (PM) linear motor, there is a force ripple which is detrimental to positioning. This force ripple is mainly due to a cogging force and a mutual force ripple. These forces are affected by the geometric parameters of a brushless PM motor, such as the width of the magnet, the height of the magnet, the shifted length of the magnetic pole, the length and height of the armature and the slot width. The optimal design can be found by considering force ripple as a cost function and the geometric parameters as design variables. In this paper, we calculate the flux density distribution in the air gap using the analytic solution of Laplace and Possion equations in the function of geometric parameters. The cogging force is obtained by integrating the Maxwell stress tensor, which is described by the flux density distribution on the slot face and end face of the iron core of an armature. Finally, a finite element method is presented in order to compare with the previous method.","PeriodicalId":37804,"journal":{"name":"Majlesi Journal of Electrical Engineering","volume":"4 1","pages":"42-47"},"PeriodicalIF":0.0,"publicationDate":"2010-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66017320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Knowledge embedded within artificial neural networks (ANNs) is distributed over the connections and weights of neurons. So, the user considers ANN as a black box system. There are many researches investigating the area of rule extraction by ANNs. In this paper, a dynamic cell structure (DCS) neural network and a modified version of LERX algorithm are used for rule extraction. On the other hand, intrusion detection system (IDS) is known as a critical technology to secure computer networks. So, the proposed algorithm is used to develop IDS and classify the patterns of intrusion. To compare the performance of the proposed system with other machine learning algorithms, multi-layer perceptron (MLP) with output weight optimization-hidden weight optimization (OWO-HWO) training algorithm is employed with selected inputs based on the results of a feature relevance analysis. Empirical results show the superior performance of the IDS based on rule extraction from DCS, in recognizing hard-detectable attack categories, e.g. userto-root (U2R) and also offering competitive false alarm rate (FAR). Although, MLP with 25 selected input features, instead of 41 standard features introduced by knowledge discovery and data mining group (KDD), performs better in terms of detection rate (DR) and cost per example (CPE) when compared with some other machine learning methods, as well.
{"title":"Intrusion Detection Based on Rule Extraction from Dynamic Cell Structure Neural Networks","authors":"M. Sheikhan, A. Khalili","doi":"10.1234/MJEE.V4I4.107","DOIUrl":"https://doi.org/10.1234/MJEE.V4I4.107","url":null,"abstract":"Knowledge embedded within artificial neural networks (ANNs) is distributed over the connections and weights of neurons. So, the user considers ANN as a black box system. There are many researches investigating the area of rule extraction by ANNs. In this paper, a dynamic cell structure (DCS) neural network and a modified version of LERX algorithm are used for rule extraction. On the other hand, intrusion detection system (IDS) is known as a critical technology to secure computer networks. So, the proposed algorithm is used to develop IDS and classify the patterns of intrusion. To compare the performance of the proposed system with other machine learning algorithms, multi-layer perceptron (MLP) with output weight optimization-hidden weight optimization (OWO-HWO) training algorithm is employed with selected inputs based on the results of a feature relevance analysis. Empirical results show the superior performance of the IDS based on rule extraction from DCS, in recognizing hard-detectable attack categories, e.g. userto-root (U2R) and also offering competitive false alarm rate (FAR). Although, MLP with 25 selected input features, instead of 41 standard features introduced by knowledge discovery and data mining group (KDD), performs better in terms of detection rate (DR) and cost per example (CPE) when compared with some other machine learning methods, as well.","PeriodicalId":37804,"journal":{"name":"Majlesi Journal of Electrical Engineering","volume":"4 1","pages":"24-34"},"PeriodicalIF":0.0,"publicationDate":"2010-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66017307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Emotion has an important role in naturalness of man-machine communication. So, computerized emotion recognition from speech is investigated by many researchers in the recent decades. In this paper, the effect of formant-related features on improving the performance of emotion detection systems is experimented. To do this, various forms and combinations of the first three formants are concatenated to a popular feature vector and Gaussian mixture models are used as classifiers. Experimental results show average recognition rate of 69% in four emotional states and noticeable performance improvement by adding only one formant-related parameter to feature vector. The architecture of hybrid emotion recognition/spotting is also proposed based on the developed models.
{"title":"EMOTION RECOGNITION AND EMOTION SPOTTING IMPROVEMENT USING FORMANT-RELATED FEATURES","authors":"D. Gharavian, M. Sheikhan","doi":"10.1234/MJEE.V4I4.266","DOIUrl":"https://doi.org/10.1234/MJEE.V4I4.266","url":null,"abstract":"Emotion has an important role in naturalness of man-machine communication. So, computerized emotion recognition from speech is investigated by many researchers in the recent decades. In this paper, the effect of formant-related features on improving the performance of emotion detection systems is experimented. To do this, various forms and combinations of the first three formants are concatenated to a popular feature vector and Gaussian mixture models are used as classifiers. Experimental results show average recognition rate of 69% in four emotional states and noticeable performance improvement by adding only one formant-related parameter to feature vector. The architecture of hybrid emotion recognition/spotting is also proposed based on the developed models.","PeriodicalId":37804,"journal":{"name":"Majlesi Journal of Electrical Engineering","volume":"4 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2010-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66017152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Here a fully 3D algorithm for automatic liver segmentation from CT volumetric datasets is presented. The algorithm starts by smoothing the original volume using anisotropic diffusion. The coarse liver region is obtained from the threshold process that is based on a priori knowledge. Then, several morphological operations is performed such as operating the liver to detach the unwanted region connected to the liver and finding the largest component using the connected component labeling (CCL) algorithm. At this stage, both 3D and 2D CCL is done subsequently. However, in 2D CCL, the adjacent slices are also affected from current slice changes. Finally, the boundary of the liver is refined using graph-cuts solver. Our algorithm does not require any user interaction or training datasets to be used. The algorithm has been evaluated on 10 CT scans of the liver and the results are encouraging to poor quality of images.
{"title":"Integration of Morphology and Graph-based Techniques for Fully Automatic Liver Segmentation","authors":"W. Yussof, H. Burkhardt","doi":"10.1234/MJEE.V4I3.322","DOIUrl":"https://doi.org/10.1234/MJEE.V4I3.322","url":null,"abstract":"Here a fully 3D algorithm for automatic liver segmentation from CT volumetric datasets is presented. The algorithm starts by smoothing the original volume using anisotropic diffusion. The coarse liver region is obtained from the threshold process that is based on a priori knowledge. Then, several morphological operations is performed such as operating the liver to detach the unwanted region connected to the liver and finding the largest component using the connected component labeling (CCL) algorithm. At this stage, both 3D and 2D CCL is done subsequently. However, in 2D CCL, the adjacent slices are also affected from current slice changes. Finally, the boundary of the liver is refined using graph-cuts solver. Our algorithm does not require any user interaction or training datasets to be used. The algorithm has been evaluated on 10 CT scans of the liver and the results are encouraging to poor quality of images.","PeriodicalId":37804,"journal":{"name":"Majlesi Journal of Electrical Engineering","volume":"4 1","pages":"59-66"},"PeriodicalIF":0.0,"publicationDate":"2010-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66017240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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