Pub Date : 2014-04-03DOI: 10.1109/ICCSP.2014.6949987
K. Sudheera, N. Nandhitha, N. Ganesh, P. Nanekar, B. Venkatraman, B. Sheela Rani
Ultrasonic Testing is the widely used NDT technique for flaw detection in thick walled weldments. It is an indirect technique and the signals are to be analyzed in order to characterize the flaw. Manual interpretation of these signals is subjective in nature and is dependent on the expertise of the individual. Hence the paradigm has shifted to automated signal analysis. In this paper a successful attempt has been made to develop a pattern among the flaws of same type without using Artificial Neural Networks. Here, the signals are analyzed with Stockwell transform and the pattern is determined. Also quantitative characterization is done with mean, standard deviation, root mean square value, peak to rms ratio.
{"title":"Feasibility of Stockwell transform for flaw pattern recognition in ultra sonic signals","authors":"K. Sudheera, N. Nandhitha, N. Ganesh, P. Nanekar, B. Venkatraman, B. Sheela Rani","doi":"10.1109/ICCSP.2014.6949987","DOIUrl":"https://doi.org/10.1109/ICCSP.2014.6949987","url":null,"abstract":"Ultrasonic Testing is the widely used NDT technique for flaw detection in thick walled weldments. It is an indirect technique and the signals are to be analyzed in order to characterize the flaw. Manual interpretation of these signals is subjective in nature and is dependent on the expertise of the individual. Hence the paradigm has shifted to automated signal analysis. In this paper a successful attempt has been made to develop a pattern among the flaws of same type without using Artificial Neural Networks. Here, the signals are analyzed with Stockwell transform and the pattern is determined. Also quantitative characterization is done with mean, standard deviation, root mean square value, peak to rms ratio.","PeriodicalId":149965,"journal":{"name":"2014 International Conference on Communication and Signal Processing","volume":"190 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117344104","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}
Pub Date : 2014-04-03DOI: 10.1109/ICCSP.2014.6949826
M. Joseph, M. S. Godwin Premi
Image retrieval is emerging as one of the important research area for browsing and retrieving images from a large database. Many image retrieval techniques are there but it suffers from low precision rates due to lighting conditions, noisy tags etc. One of the most important problems that we have seen in image retrieval is the semantic gap. This paper proposes a new method for improving the performance of image retrieval system and reducing the semantic gap using Auxiliary Visual Word and Tag refinement. Here the retrieval accuracy gets improved by the discovery of contextual features. This paper also provides an image pre-processing technique using Contrast Limited Adaptive Histogram Equalization algorithm and image ranking approach. It also describes about effective and efficient distance measure and a minimum distance classification for retrieval. The experimental results show that precision has been improved with the proposed method.
{"title":"Contextual feature discovery and image ranking for image object retrieval and Tag refinement","authors":"M. Joseph, M. S. Godwin Premi","doi":"10.1109/ICCSP.2014.6949826","DOIUrl":"https://doi.org/10.1109/ICCSP.2014.6949826","url":null,"abstract":"Image retrieval is emerging as one of the important research area for browsing and retrieving images from a large database. Many image retrieval techniques are there but it suffers from low precision rates due to lighting conditions, noisy tags etc. One of the most important problems that we have seen in image retrieval is the semantic gap. This paper proposes a new method for improving the performance of image retrieval system and reducing the semantic gap using Auxiliary Visual Word and Tag refinement. Here the retrieval accuracy gets improved by the discovery of contextual features. This paper also provides an image pre-processing technique using Contrast Limited Adaptive Histogram Equalization algorithm and image ranking approach. It also describes about effective and efficient distance measure and a minimum distance classification for retrieval. The experimental results show that precision has been improved with the proposed method.","PeriodicalId":149965,"journal":{"name":"2014 International Conference on Communication and Signal Processing","volume":"226 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122064006","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}
Pub Date : 2014-04-03DOI: 10.1109/ICCSP.2014.6950119
P. Dash, S. S. Pujari, Yougajyoty Sahoo
Identification is a genuine fact that resembles in any kind of systems, whether it may be a control, compute or communication systems. System identification is a proposed area that establish the mathematical model of the system which helps for modeling and identification of an unknown system. This paper is focused on design and synthesis of Adaptive System Identification based on LMS algorithm with ALTERA QUARTUS II development platform and implemented on CYCLONE II EP2C35F672C8 Field Programming Gate Array (FPGA). Architecture of adaptive filter that is based on multiplier and adder is to realize the MAC operation of the Finite Impulse Response (FIR). The coefficients of the adaptive filter are adjusted automatically by Least Mean Square (LMS) algorithm based on input signals. For this cause adaptive filter is more important for system identification. The design is also experienced in Model based Design approach with the help of Xilinx System Generator for the application of Adaptive System Identification.
识别是一个真实的事实，类似于任何类型的系统，无论是控制系统、计算系统还是通信系统。系统识别是建立系统数学模型的一个领域，它有助于对未知系统的建模和识别。本文在ALTERA QUARTUS II开发平台上设计和合成了基于LMS算法的自适应系统辨识系统，并在CYCLONE II EP2C35F672C8 FPGA上实现。基于乘法器和加法器的自适应滤波器结构是为了实现有限脉冲响应(FIR)的MAC运算。基于输入信号，采用最小均方算法自动调整自适应滤波器的系数。因此，自适应滤波器在系统辨识中显得尤为重要。本设计还利用基于模型的设计方法，结合Xilinx System Generator实现了自适应系统辨识的应用。
{"title":"Design and implementation of single order LMS based adaptive system identification on altera based cyclone II FPGA","authors":"P. Dash, S. S. Pujari, Yougajyoty Sahoo","doi":"10.1109/ICCSP.2014.6950119","DOIUrl":"https://doi.org/10.1109/ICCSP.2014.6950119","url":null,"abstract":"Identification is a genuine fact that resembles in any kind of systems, whether it may be a control, compute or communication systems. System identification is a proposed area that establish the mathematical model of the system which helps for modeling and identification of an unknown system. This paper is focused on design and synthesis of Adaptive System Identification based on LMS algorithm with ALTERA QUARTUS II development platform and implemented on CYCLONE II EP2C35F672C8 Field Programming Gate Array (FPGA). Architecture of adaptive filter that is based on multiplier and adder is to realize the MAC operation of the Finite Impulse Response (FIR). The coefficients of the adaptive filter are adjusted automatically by Least Mean Square (LMS) algorithm based on input signals. For this cause adaptive filter is more important for system identification. The design is also experienced in Model based Design approach with the help of Xilinx System Generator for the application of Adaptive System Identification.","PeriodicalId":149965,"journal":{"name":"2014 International Conference on Communication and Signal Processing","volume":"55 18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124041563","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}
Pub Date : 2014-04-03DOI: 10.1109/ICCSP.2014.6950143
I. Nelson, K. S. Vishvaksenan, V. Rajendran
In this correspondence, we consider the performance of Multi-Input Multi-Output (MIMO) assisted multi-carrier (MC) modulated system for the transmission of the acoustic signal in underwater communications. In underwater communications, acoustic interference and ambient noise are the two major channel impairments. In our work, we consider turbo code as channel encoder and at the receiver, we employ iterative decoding algorithm to alleviate the effects of ambient noise and acoustic interference. We implement IFFT block at the transmitter and FFT block at the receiver to realize multi-carrier modulation. Particularly, we investigate the effects of eleven tap delay pertaining to shallow water model in the context of coded MIMO-OFDM system. At the receiver, we realize non-linear detector based on zero-forcing (ZF) algorithm. It is shown through simulation results that MIMO-OFDM system with ZF algorithm provides achievable bit error rate with less signal-to-noise ratio using iterative decoding algorithm..
{"title":"Performance of turbo coded MIMO-OFDM system for underwater communications","authors":"I. Nelson, K. S. Vishvaksenan, V. Rajendran","doi":"10.1109/ICCSP.2014.6950143","DOIUrl":"https://doi.org/10.1109/ICCSP.2014.6950143","url":null,"abstract":"In this correspondence, we consider the performance of Multi-Input Multi-Output (MIMO) assisted multi-carrier (MC) modulated system for the transmission of the acoustic signal in underwater communications. In underwater communications, acoustic interference and ambient noise are the two major channel impairments. In our work, we consider turbo code as channel encoder and at the receiver, we employ iterative decoding algorithm to alleviate the effects of ambient noise and acoustic interference. We implement IFFT block at the transmitter and FFT block at the receiver to realize multi-carrier modulation. Particularly, we investigate the effects of eleven tap delay pertaining to shallow water model in the context of coded MIMO-OFDM system. At the receiver, we realize non-linear detector based on zero-forcing (ZF) algorithm. It is shown through simulation results that MIMO-OFDM system with ZF algorithm provides achievable bit error rate with less signal-to-noise ratio using iterative decoding algorithm..","PeriodicalId":149965,"journal":{"name":"2014 International Conference on Communication and Signal Processing","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125871479","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}
Pub Date : 2014-04-03DOI: 10.1109/ICCSP.2014.6950134
Nookala Venu
In this paper, a new segmentation algorithm with the integration of mean and peak-and-valley filtering based denoising and Gaussian kernels based fuzzy c-means (MPVKFCM) algorithm is proposed for medical image segmentation. First, the image is denoised by using the mean and peak-and-valley filtering algorithm. Secondly, image segmentation algorithm with Gaussian kernels based fuzzy c-means is performed on the denoised image. The performance of the proposed algorithm is tested on OASIS-MRI image dataset. The performance is tested in terms of score, number of iterations (NI), Execution time and (TM) under different Gaussian noises on OASIS-MRI dataset. The results after investigation, the proposed method shows a significant improvement as compared to other existing methods in terms of Score, NI and TM under different Gaussian noises on OASIS-MRI dataset.
{"title":"Performance and evalution of Guassian kernals for FCM algorithm with mean filtering based denoising for MRI segmentation","authors":"Nookala Venu","doi":"10.1109/ICCSP.2014.6950134","DOIUrl":"https://doi.org/10.1109/ICCSP.2014.6950134","url":null,"abstract":"In this paper, a new segmentation algorithm with the integration of mean and peak-and-valley filtering based denoising and Gaussian kernels based fuzzy c-means (MPVKFCM) algorithm is proposed for medical image segmentation. First, the image is denoised by using the mean and peak-and-valley filtering algorithm. Secondly, image segmentation algorithm with Gaussian kernels based fuzzy c-means is performed on the denoised image. The performance of the proposed algorithm is tested on OASIS-MRI image dataset. The performance is tested in terms of score, number of iterations (NI), Execution time and (TM) under different Gaussian noises on OASIS-MRI dataset. The results after investigation, the proposed method shows a significant improvement as compared to other existing methods in terms of Score, NI and TM under different Gaussian noises on OASIS-MRI dataset.","PeriodicalId":149965,"journal":{"name":"2014 International Conference on Communication and Signal Processing","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124650675","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}
Pub Date : 2014-04-03DOI: 10.1109/ICCSP.2014.6950112
Dixit V. Bhoraniya, R. Kher
Ambulatory ECG signal monitoring is useful when long term cardiac monitoring of a patient is necessary. Ambulatory ECG (A-ECG) monitoring provides electrical activity of the heart while a person is involved in doing his or her normal routine activities. Thus, the recorded ECG signal consists of cardiac signal along with motion artifacts introduced due to person's body movements during routine activities. This motion artifact has spectral overlap with cardiac signal in 1-10 Hz which corresponds to ECG features like P wave and T wave. Detection of motion artifacts due to different physical activities (PA) might help in further cardiac diagnosis. Ambulatory ECG signal analysis for detection of various motion artifacts using discrete wavelet transform (DWT) approach is addressed in this paper. The ECG signals of healthy subjects (aged of 19 to 16 years) were recorded while the person performs various body movements activity like (i) up and down movement of left hand, (ii) up and down movement of right hand, (iii) waist twisting movement while standing and (iv) change in position from sitting down on chair to standing up movement in lead I configuration by using BIOPAC MP 36 signal acquiring system.
{"title":"Motion artifacts extraction using dwt from ambulatory ECG (A-ECG)","authors":"Dixit V. Bhoraniya, R. Kher","doi":"10.1109/ICCSP.2014.6950112","DOIUrl":"https://doi.org/10.1109/ICCSP.2014.6950112","url":null,"abstract":"Ambulatory ECG signal monitoring is useful when long term cardiac monitoring of a patient is necessary. Ambulatory ECG (A-ECG) monitoring provides electrical activity of the heart while a person is involved in doing his or her normal routine activities. Thus, the recorded ECG signal consists of cardiac signal along with motion artifacts introduced due to person's body movements during routine activities. This motion artifact has spectral overlap with cardiac signal in 1-10 Hz which corresponds to ECG features like P wave and T wave. Detection of motion artifacts due to different physical activities (PA) might help in further cardiac diagnosis. Ambulatory ECG signal analysis for detection of various motion artifacts using discrete wavelet transform (DWT) approach is addressed in this paper. The ECG signals of healthy subjects (aged of 19 to 16 years) were recorded while the person performs various body movements activity like (i) up and down movement of left hand, (ii) up and down movement of right hand, (iii) waist twisting movement while standing and (iv) change in position from sitting down on chair to standing up movement in lead I configuration by using BIOPAC MP 36 signal acquiring system.","PeriodicalId":149965,"journal":{"name":"2014 International Conference on Communication and Signal Processing","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124757169","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}
Pub Date : 2014-04-03DOI: 10.1109/ICCSP.2014.6949980
M. Soni, P. Dakhole
CAM (content-addressable memory) is a specialized type of high-speed memory that searches its entire contents in a single clock cycle. We are designing generalized CAM using Dual Port RAM (random access memory) structure which will perform match operation in addition to read and write operation .The design has fast search capabilities while consuming least system resources as possible. CAM provides performance advantage over other search algorithms as searching is based on content rather than address unlike RAM. The match time of our CAM structure is faster and resources are more effective. CAM is used in application where search time is very critical. content addressable memory compare input search data against stored data and return address of matched data. Thus overall function of CAM is to take search word and return matching memory location.
{"title":"FPGA implementation of content addressable memory based information detection system","authors":"M. Soni, P. Dakhole","doi":"10.1109/ICCSP.2014.6949980","DOIUrl":"https://doi.org/10.1109/ICCSP.2014.6949980","url":null,"abstract":"CAM (content-addressable memory) is a specialized type of high-speed memory that searches its entire contents in a single clock cycle. We are designing generalized CAM using Dual Port RAM (random access memory) structure which will perform match operation in addition to read and write operation .The design has fast search capabilities while consuming least system resources as possible. CAM provides performance advantage over other search algorithms as searching is based on content rather than address unlike RAM. The match time of our CAM structure is faster and resources are more effective. CAM is used in application where search time is very critical. content addressable memory compare input search data against stored data and return address of matched data. Thus overall function of CAM is to take search word and return matching memory location.","PeriodicalId":149965,"journal":{"name":"2014 International Conference on Communication and Signal Processing","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124794937","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}
Pub Date : 2014-04-03DOI: 10.1109/ICCSP.2014.6950061
Jaba Deva Krupa Abel, Y. Karuna, G. Ramachandra Reddy, R. Dhuli
Multicarrier modulation (MCM) is a popularly used transmission technique. This paper aims at designing the multicarrier modulation pulse for communication over a Doubly Dispersive (DD) channel. For a DD channel, Inter Symbol Interference (ISI)Inter Carrier Interference (ICI) can be completely eliminated only when we design the pulses with the knowledge of the channel state. But for a quickly varying doubly dispersive channel, the channel state cannot be tracked by the transmitter. So instead of designing a pulse which suppresses all the ISIICI, the proposed technique designs the MCM pulses which allows a tolerable ISIICI within the target pattern and eliminates all the ISIICI outside the target pattern. By properly selecting the target pattern, it is possible to treat the allowed ISIICI by using simple equalization/decoding techniques.
{"title":"Design of multicarrier pulses maximizing SINR by ISI/ICI shaping for the Doubly Dispersive channel","authors":"Jaba Deva Krupa Abel, Y. Karuna, G. Ramachandra Reddy, R. Dhuli","doi":"10.1109/ICCSP.2014.6950061","DOIUrl":"https://doi.org/10.1109/ICCSP.2014.6950061","url":null,"abstract":"Multicarrier modulation (MCM) is a popularly used transmission technique. This paper aims at designing the multicarrier modulation pulse for communication over a Doubly Dispersive (DD) channel. For a DD channel, Inter Symbol Interference (ISI)Inter Carrier Interference (ICI) can be completely eliminated only when we design the pulses with the knowledge of the channel state. But for a quickly varying doubly dispersive channel, the channel state cannot be tracked by the transmitter. So instead of designing a pulse which suppresses all the ISIICI, the proposed technique designs the MCM pulses which allows a tolerable ISIICI within the target pattern and eliminates all the ISIICI outside the target pattern. By properly selecting the target pattern, it is possible to treat the allowed ISIICI by using simple equalization/decoding techniques.","PeriodicalId":149965,"journal":{"name":"2014 International Conference on Communication and Signal Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129885492","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}
Pub Date : 2014-04-03DOI: 10.1109/ICCSP.2014.6949859
D. Rangaprakash, D. Dutt
Wrist pulse signal contains more important information about the health status of a person and pulse signal diagnosis has been employed in oriental medicine since very long time. In this paper we have used signal processing techniques to extract information from wrist pulse signals. For this purpose we have acquired radial artery pulse signals at wrist position noninvasively for different cases of interest. The wrist pulse waveforms have been analyzed using spatial features. Results have been obtained for the case of wrist pulse signals recorded for several subjects before exercise and after exercise. It is shown that the spatial features show statistically significant changes for the two cases and hence they are effective in distinguishing the changes taking place due to exercise. Support vector machine classifier is used to classify between the groups, and a high classification accuracy of 99.71% is achieved. Thus this paper demonstrates the utility of the spatial features in studying wrist pulse signals obtained under various recording conditions. The ability of the model to distinguish changes occurring under two different recording conditions can be potentially used for healthcare applications.
{"title":"Analysis of wrist pulse signals using spatial features in time domain","authors":"D. Rangaprakash, D. Dutt","doi":"10.1109/ICCSP.2014.6949859","DOIUrl":"https://doi.org/10.1109/ICCSP.2014.6949859","url":null,"abstract":"Wrist pulse signal contains more important information about the health status of a person and pulse signal diagnosis has been employed in oriental medicine since very long time. In this paper we have used signal processing techniques to extract information from wrist pulse signals. For this purpose we have acquired radial artery pulse signals at wrist position noninvasively for different cases of interest. The wrist pulse waveforms have been analyzed using spatial features. Results have been obtained for the case of wrist pulse signals recorded for several subjects before exercise and after exercise. It is shown that the spatial features show statistically significant changes for the two cases and hence they are effective in distinguishing the changes taking place due to exercise. Support vector machine classifier is used to classify between the groups, and a high classification accuracy of 99.71% is achieved. Thus this paper demonstrates the utility of the spatial features in studying wrist pulse signals obtained under various recording conditions. The ability of the model to distinguish changes occurring under two different recording conditions can be potentially used for healthcare applications.","PeriodicalId":149965,"journal":{"name":"2014 International Conference on Communication and Signal Processing","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128266467","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}
Pub Date : 2014-04-03DOI: 10.1109/ICCSP.2014.6949920
C. N. Devi, A. Chandrasekharan, V. Sundararaman, Z. C. Alex
This paper provides an overview of magnetic resonance imaging of the neonatal brain, presents the challenges involved in segmenting the neonatal brain images and reviews the existing techniques for automatic segmentation, including atlas-based probabilistic segmentations and morphology based brain segmentation. It compares the various methods in practice and highlights their limitations, particularly the inadequacies in segmenting the myelinated portions of the brain. It also proposes a new approach to overcome these shortcomings.
{"title":"Automatic segmentation of neonatal brain magnetic resonance images","authors":"C. N. Devi, A. Chandrasekharan, V. Sundararaman, Z. C. Alex","doi":"10.1109/ICCSP.2014.6949920","DOIUrl":"https://doi.org/10.1109/ICCSP.2014.6949920","url":null,"abstract":"This paper provides an overview of magnetic resonance imaging of the neonatal brain, presents the challenges involved in segmenting the neonatal brain images and reviews the existing techniques for automatic segmentation, including atlas-based probabilistic segmentations and morphology based brain segmentation. It compares the various methods in practice and highlights their limitations, particularly the inadequacies in segmenting the myelinated portions of the brain. It also proposes a new approach to overcome these shortcomings.","PeriodicalId":149965,"journal":{"name":"2014 International Conference on Communication and Signal Processing","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127425618","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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