Enhanced brain image retrieval using carrier frequency offset compensated orthogonal frequency division multiplexing for telemedicine applications

Chitra, S.; Kumaratharan, N.; Ramesh, S.

doi:10.1002/ima.22269

Cited by 7 publications

(3 citation statements)

References 19 publications

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“…The size of the image considered for the simulation is 128 × 128 shown in Figure 15A. It clearly shows that the presence of CFO degrades the image quality, 26 shown in Figure 15B. The reconstructed image in Figure 15C,D,E shows that the proposed algorithm offers better quality image compared to MUSIC and MLE.…”

Section: Resultsmentioning

confidence: 96%

A novel subspace method for precise carrier frequency offset estimation in multicarrier modulation scheme under multiuser environment

Chitra¹,

Kumaratharan²,

Ramesh

2020

Int J Communication

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Summary In recent years, the demand on data communication is rapidly increasing, and there is a need of spectrally efficient modulation scheme for massive data transmissions. Multicarrier modulation (MCM) is widely used in wireless systems to support high data rate multimedia services such as audio, video, image, and data. Multicarrier code division multiple access (MC‐CDMA) is one of the MCM techniques which combines the best features of orthogonal frequency division multiplexing (OFDM) and code division multiple access (CDMA). The carrier frequency offset (CFO) due to oscillator instabilities or Doppler shifts greatly deteriorates the performance of MC‐CDMA system. Hence, the subcarriers are no longer orthogonal and introduce intercarrier interference (ICI) at the receiver. The simultaneous CFO estimation and compensation in multiuser mobile environment are a challenging task which needs to be addressed for optimum performance. The blind CFO estimation such as maximum likelihood estimation (MLE) has limited estimation range which is less than half the subcarrier spacing. Multiple signal classification (MUSIC) is the spectral estimation‐based subspace method suited for simultaneous CFO estimation in the multiuser environment. MUSIC offers precise CFO estimation only for the well‐spaced CFOs and fails to discriminate the strictly spaced CFOs. Hence, a novel subspace method is proposed in this paper to improve the estimation accuracy for closely spaced CFOs with the reduced computational complexity. Simulation results show that the proposed enhanced root MUSIC estimation outperforms MLE and MUSIC in terms of estimation accuracy, bit error rate (BER), and ICI power.

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Section: Resultsmentioning

confidence: 96%

A novel subspace method for precise carrier frequency offset estimation in multicarrier modulation scheme under multiuser environment

Chitra¹,

Kumaratharan²,

Ramesh

2020

Int J Communication

Self Cite

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“…Cruz et al [23] developed a mobile teleradiology system that is suitable for facilitating the CBMIR process. Chitra et al [24] proposed an improved retrieval algorithm for brain images using carrier frequency offset compensated OFDM technique for telemedicine scenarios. Jiang et al [25] tried to solve the "semantic gap" of the CBMIR using the crowdsourcing model in the MTN, which is empirically verified to be both successful and efficient.…”

Section: Pr Jmentioning

confidence: 99%

Progressive Distributed and Parallel Similarity Retrieval of Large CT Image Sequences in Mobile Telemedicine Networks

Zhuang

Jiang

2022

Wireless Communications and Mobile Computing

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Computed tomography image (CTI) sequence is essentially a time-series data that typically consists of a large amount of nearby and similar CTIs. Due to the high communication and computational costs, it is difficult to perform a progressive distributed similarity retrieval of the large CTI sequence (CTIS)s, particularly in resource-constraint mobile telemedicine network (MTN)s. In this paper, we present a Dprs method—progressive distributed and parallel similarity retrieval scheme for the CTISs in the MTN. To the best of our knowledge, there is little research on the Dprs processing, especially in the MTN. Four supporting techniques (i.e., (1) PCTI-based similarity measurement, (2) lightweight privacy-preserving strategy, (3) SSL-based data distribution scheme, and (4) the UDI framework) are developed. The experimental evaluation indicates that our proposed Dprs method is more progressive than the state of the art, with a significant reduction in response time.

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“…A mobile teleradiology system [ 27 ] is appropriate for streamlining the CBMIR procedure. For telemedicine applications, Chitra et al [ 28 ] suggested an enhanced retrieval approach for brain images utilizing carrier frequency offset adjusted OFDM technique. To solve the ‘ semantic gap ’, Jiang et al [ 29 ] introduced a novel framework of mobile similarity retrieval of medical images based on a crowdsourcing model.…”

Section: Introductionmentioning

confidence: 99%

Progressive privacy-preserving batch retrieval of lung CT image sequences based on edge-cloud collaborative computation

Zhuang

Jiang

2022

PLoS ONE

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Background A computer tomography image (CI) sequence can be regarded as a time-series data that is composed of a great deal of nearby and similar CIs. Since the computational and I/O costs of similarity measure, encryption, and decryption calculation during a similarity retrieval of the large CI sequences (CIS) are extremely high, deploying all retrieval tasks in the cloud, however, will lead to excessive computing load on the cloud, which will greatly and negatively affect the retrieval performance. Methodologies To tackle the above challenges, the paper proposes a progressive privacy-preserving Batch Retrieval scheme for the lung CISs based on edge-cloud collaborative computation called the BRS method. There are four supporting techniques to enable the BRS method, such as: 1) batch similarity measure for CISs, 2) CIB-based privacy preserving scheme, 3) uniform edge-cloud index framework, and 4) edge buffering. Results The experimental results reveal that our method outperforms the state-of-the-art approaches in terms of efficiency and scalability, drastically reducing response time by lowering network communication costs while enhancing retrieval safety and accuracy.

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Enhanced brain image retrieval using carrier frequency offset compensated orthogonal frequency division multiplexing for telemedicine applications

Cited by 7 publications

References 19 publications

A novel subspace method for precise carrier frequency offset estimation in multicarrier modulation scheme under multiuser environment

A novel subspace method for precise carrier frequency offset estimation in multicarrier modulation scheme under multiuser environment

Progressive Distributed and Parallel Similarity Retrieval of Large CT Image Sequences in Mobile Telemedicine Networks

Progressive privacy-preserving batch retrieval of lung CT image sequences based on edge-cloud collaborative computation

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