Sensor grid applications in patient monitoring. - Pallikonda Rajasekaran Murugan; S. Radhakrishnan; P. Subbaraj (Future Gener. Comput. Syst., 2010)

A Novel Approach for Information Security in Ad Hoc Networks through Secure Key Management. - S. Suma Christal Mary; M. Pallikonda Rajasekaran; Y. ChrisbinJeeva (J. Comput. Sci., 2013)

PET image reconstruction using ANN. - Thiyagarajan Arunprasath; Rajasekaran Murugan Pallikonda; Subramanian Kannan (Int. J. Imaging Syst. Technol., 2014)

A complete automated algorithm for segmentation of tissues and identification of tumor region in T1, T2, and FLAIR brain images using optimization and clustering techniques. - Vishnuvarthanan Govindaraj; Pallikonda Rajasekaran Murugan (Int. J. Imaging Syst. Technol., 2014)

ANFIS-EM approach for PET brain image reconstruction. - Thiyagarajan Arunprasath; Pallikonda Rajasekaran Murugan; Kannan Subramanian (Int. J. Imaging Syst. Technol., 2015)

Efficient image compression techniques for compressing multimodal medical images using neural network radial basis function approach. - Balasubramani Perumal; Pallikonda Rajasekaran Murugan (Int. J. Imaging Syst. Technol., 2015)

Analysis of Particle Swarm Optimization Based 2D FIR Filter for Reduction of Additive and Multiplicative Noise in Images. - V. Muneeswaran; M. Pallikonda Rajasekaran (ICTCSDM, 2016)

Efficient Hybrid Approach for Compression of Multi Modal Medical Images. - Balasubramani Perumal; M. Pallikonda Rajasekaran; Thiyagarajan Arun Prasath (ICTCSDM, 2016)

An unsupervised learning method with a clustering approach for tumor identification and tissue segmentation in magnetic resonance brain images. - Vishnuvarthanan Govindaraj; Pallikonda Rajasekaran Murugan; P. Subbaraj; Anitha Vishnuvarthanan (Appl. Soft Comput., 2016)

An automated hybrid approach using clustering and nature inspired optimization technique for improved tumor and tissue segmentation in magnetic resonance brain images. - Anitha Vishnuvarthanan; M. Pallikonda Rajasekaran; Vishnuvarthanan Govindaraj; Yudong Zhang 001; Arunprasath Thiyagarajan (Appl. Soft Comput., 2017)

Tumor detection in T1, T2, FLAIR and MPR brain images using a combination of optimization and fuzzy clustering improved by seed-based region growing algorithm. - Vishnuvarthanan Govindaraj; Pallikonda Rajasekaran Murugan; Anitha Vishnuvarthanan; Thiyagarajan Arun Prasath; M. Kannan (Int. J. Imaging Syst. Technol., 2017)

Offline Analysis for Designing Electrooculogram Based Human Computer Interface Control for Paralyzed Patients. - Gu Jialu; S. Ramkumar; G. Emayavaramban; M. Thilagaraj; V. Muneeswaran; M. Pallikonda Rajasekaran; Ahmed Faeq Hussein (IEEE Access, 2018)

Computer-aided automated discrimination of Alzheimer's disease and its clinical progression in magnetic resonance images using hybrid clustering and game theory-based classification strategies. - P. Rajesh Kumar; Thiyagarajan Arunprasath; Pallikonda Rajasekaran Murugan; Vishnuvarthanan Govindaraj (Comput. Electr. Eng., 2018)

Real time reactive power compensation for battery/photovoltaic hybrid power source for internet of hybrid electric vehicle system. - N. Pothirasan; M. Pallikonda Rajasekaran; V. Muneeswaran (Cogn. Syst. Res., 2018)

Development of a combinational framework to concurrently perform tissue segmentation and tumor identification in T1 - W, T2 - W, FLAIR and MPR type magnetic resonance brain images. - Anitha Vishnuvarthanan; M. Pallikonda Rajasekaran; Vishnuvarthanan Govindaraj; Yudong Zhang 001; Arunprasath Thiyagarajan (Expert Syst. Appl., 2018)

Brain Computer Interface for Neurodegenerative Person Using Electroencephalogram. - Junwei Li; S. Ramkumar; G. Emayavaramban; D. Franklin Vinod; M. Thilagaraj; V. Muneeswaran; M. Pallikonda Rajasekaran; V. Venkataraman; Ahmed Faeq Hussein (IEEE Access, 2019)

Tsallis entropy: as a new single feature with the least computation time for classification of epileptic seizures. - M. Thilagaraj; M. Pallikonda Rajasekaran; N. Arun Kumar (Clust. Comput., 2019)

Analysis and classification of malignancy in pancreatic magnetic resonance images using neural network techniques. - Aruna Devi Balasubramanian; Pallikonda Rajasekaran Murugan; Arun Prasath Thiyagarajan (Int. J. Imaging Syst. Technol., 2019)

Unsupervised learning-based clustering approach for smart identification of pathologies and segmentation of tissues in brain magnetic resonance imaging. - Vigneshwaran Senthilvel; Vishnuvarthanan Govindaraj; Pallikonda Rajasekaran Murugan; Yudong Zhang 001; Thiyagarajan Arun Prasath (Int. J. Imaging Syst. Technol., 2019)

An empirical mode decomposition (EMD)-based scheme for alcoholism identification. - M. Thilagaraj; M. Pallikonda Rajasekaran (Pattern Recognit. Lett., 2019)

Automatic segmentation of gallbladder using bio-inspired algorithm based on a spider web construction model. - V. Muneeswaran; M. Pallikonda Rajasekaran (J. Supercomput., 2019)

Automated unsupervised learning-based clustering approach for effective anomaly detection in brain magnetic resonance imaging (MRI). - Vishnuvarthanan Govindaraj; Arunprasath Thiyagarajan; M. Pallikonda Rajasekaran; Yudong Zhang 001; Rajesh Krishnasamy (IET Image Process., 2020)

Automatic knee joint segmentation using Douglas-Rachford splitting method. - C. Rini; Balasubramani Perumal; Pallikonda Rajasekaran Murugan (Multim. Tools Appl., 2020)

A smartly designed automated map based clustering algorithm for the enhanced diagnosis of pathologies in brain MR images. - Vigneshwaran Senthilvel; Vishnuvarthanan Govindaraj; Yu-Dong Zhang 001; Pallikonda Rajasekaran Murugan; Arun Prasath Thiyagarajan (Expert Syst. J. Knowl. Eng., 2021)

Smart Identification of Topographically Variant Anomalies in Brain Magnetic Resonance Imaging Using a Fish School-Based Fuzzy Clustering Approach. - Saravanan Alagarsamy; Yudong Zhang 001; Vishnuvarthanan Govindaraj; Rajasekaran Murugan Pallikonda; Sakthivel Sankaran (IEEE Trans. Fuzzy Syst., 2021)

A hybrid deep learning based brain tumor classification and segmentation by stationary wavelet packet transform and adaptive kernel fuzzy c means clustering. - R. Sindhiya Devi; Balasubramani Perumal; M. Pallikonda Rajasekaran (Adv. Eng. Softw., 2022)

Minimally parametrized segmentation framework with dual metaheuristic optimisation algorithms and FCM for detection of anomalies in MR brain images. - Senthilkumar Natarajan; Vishnuvarthanan Govindaraj; Yudong Zhang 001; Pallikonda Rajasekaran Murugan; Kannapiran Balasubramanian; Karunanithi Kandasamy; Khurram Ejaz (Biomed. Signal Process. Control., 2022)

A biologically-inspired hybrid deep learning approach for brain tumor classification from magnetic resonance imaging using improved gabor wavelet transform and Elmann-BiLSTM network. - S. K. Rajeev; M. Pallikonda Rajasekaran; Vishnuvarthanan Govindaraj; Thiyagarajan Arunprasath (Biomed. Signal Process. Control., 2022)

Agnostic multimodal brain anomalies detection using a novel single-structured framework for better patient diagnosis and therapeutic planning in clinical oncology. - Kottaimalai Ramaraj; Vishnuvarthanan Govindaraj; Yu-Dong Zhang 001; Pallikonda Rajasekaran Murugan; Shui-Hua Wang; Arunprasath Thiyagarajan; Sakthivel Sankaran (Biomed. Signal Process. Control., 2022)

Multiscale Laplacian graph kernel features combined with tree deep convolutional neural network for the detection of ECG arrhythmia. - M. Ramkumar 001; A. Lakshmi; M. Pallikonda Rajasekaran; A. Manjunathan (Biomed. Signal Process. Control., 2022)

A novel triple-level combinational framework for brain anomaly segmentation to augment clinical diagnosis. - Senthilkumar Natarajan; Vishnuvarthanan Govindaraj; Ravipudi Venkata Rao Narayana; Yu-Dong Zhang 001; Pallikonda Rajasekaran Murugan; Karunanithi Kandasamy; Khurram Ejaz (Comput. methods Biomech. Biomed. Eng. Imaging Vis., 2022)

A robust hybrid fusion segmentation approach for automated tumor diagnosis and classification in brain MR images. - R. Sindhiya Devi; Balasubramani Perumal; M. Pallikonda Rajasekaran (J. Intell. Fuzzy Syst., 2022)

Development of scalable coding for the encryption and decryption of images using modified diagonal min-max block truncation code. - Jeya Bright Pankiraj; Vishnuvarthanan Govindaraj; Yudong Zhang 001; Pallikonda Rajasekaran Murugan; Anisha Milton (Multim. Tools Appl., 2023)

Development of scalable coding on encrypted images using BTC for different non-overlapping block size. - Jeya Bright Pankiraj; Vishnuvarthanan Govindaraj; Yudong Zhang 001; Pallikonda Rajasekaran Murugan; Kottaimalai Ramaraj (Signal Image Video Process., 2023)

Hybrid D-OCapNet: Automated Multi-Class Alzheimer's Disease Classification in Brain MRI Using Hybrid Dense Optimal Capsule Network. - A. V. Nisha; M. Pallikonda Rajasekaran; Kottaimalai Ramaraj; Vishnuvarthanan Govindaraj; Thiyagarajan Arunprasath; V. Muneeswaran (Int. J. Pattern Recognit. Artif. Intell., 2023)

Glioma detection using EHO based FLAME clustering in MR brain images. - Baiju Karun; Thiyagarajan Arun Prasath; M. Pallikonda Rajasekaran; Rakhee Makreri (Int. J. Imaging Syst. Technol., 2024)

Development of scalable coding of encrypted images using Modified Absolute Moment Block Truncation Code. - Jeya Bright Pankiraj; Vishnuvarthanan Govindaraj; Yu-Dong Zhang 001; Pallikonda Rajasekaran Murugan; Kottaimalai Ramaraj; Paras Jain 005; Arunprasath Thiagarajan (Signal Image Video Process., 2024)

LMGU-NET: methodological intervention for prediction of bone health for clinical recommendations. - Gautam Amiya; Pallikonda Rajasekaran Murugan; Kottaimalai Ramaraj; Vishnuvarthanan Govindaraj; Muneeswaran Vasudevan; M. Thirumurugan; S. Sheik Abdullah; Arunprasath Thiyagarajan (J. Supercomput., 2024)

Expeditious detection and segmentation of bone mass variation in DEXA images using the hybrid GLCM-AlexNet approach. - Gautam Amiya; Pallikonda Rajasekaran Murugan; Kottaimalai Ramaraj; Vishnuvarthanan Govindaraj; Muneeswaran Vasudevan; M. Thirumurugan; Yu-Dong Zhang 001; S. Sheik Abdullah; Arunprasath Thiyagarajan (Soft Comput., 2024)