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Thiyagarajan Arunprasath
Person information
- affiliation: Kalasalingam Academy of Research and Education, School of Electronics and Electrical Technology, Tamil Nadu, India
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2020 – today
- 2024
- [j18]Muthuvel Arumugam
, Arunprasath Thiyagarajan, Lakshmi Adhi, Shyamala Alagar:
Crossover smell agent optimized multilayer perceptron for precise brain tumor classification on MRI images. Expert Syst. Appl. 238(Part B): 121453 (2024) - [j17]Baiju Karun
Glioma detection using EHO based FLAME clustering in MR brain images. Int. J. Imaging Syst. Technol. 34(1) (2024) - [j16]Gautam Amiya, Pallikonda Rajasekaran Murugan, Kottaimalai Ramaraj, Vishnuvarthanan Govindaraj, Muneeswaran Vasudevan, M. Thirumurugan, Yu-Dong Zhang, S. Sheik Abdullah, Arunprasath Thiyagarajan:
Expeditious detection and segmentation of bone mass variation in DEXA images using the hybrid GLCM-AlexNet approach. Soft Comput. 28(19): 11633-11646 (2024) - [j15]Gautam Amiya, Pallikonda Rajasekaran Murugan, Kottaimalai Ramaraj, Vishnuvarthanan Govindaraj, Muneeswaran Vasudevan, M. Thirumurugan, S. Sheik Abdullah, Arunprasath Thiyagarajan:
LMGU-NET: methodological intervention for prediction of bone health for clinical recommendations. J. Supercomput. 80(11): 15636-15663 (2024) - 2023
- [j14]A. V. Nisha
Hybrid D-OCapNet: Automated Multi-Class Alzheimer's Disease Classification in Brain MRI Using Hybrid Dense Optimal Capsule Network. Int. J. Pattern Recognit. Artif. Intell. 37(15): 2356025:1-2356025:33 (2023) - 2022
- [j13]Kottaimalai Ramaraj, Vishnuvarthanan Govindaraj, Yu-Dong Zhang
Agnostic multimodal brain anomalies detection using a novel single-structured framework for better patient diagnosis and therapeutic planning in clinical oncology. Biomed. Signal Process. Control. 77: 103786 (2022) - [j12]S. K. Rajeev, M. Pallikonda Rajasekaran, Vishnuvarthanan Govindaraj, Thiyagarajan Arunprasath:
A biologically-inspired hybrid deep learning approach for brain tumor classification from magnetic resonance imaging using improved gabor wavelet transform and Elmann-BiLSTM network. Biomed. Signal Process. Control. 78: 103949 (2022) - 2021
- [j11]Vigneshwaran Senthilvel
A smartly designed automated map based clustering algorithm for the enhanced diagnosis of pathologies in brain MR images. Expert Syst. J. Knowl. Eng. 38(2) (2021) - 2020
- [j10]Vishnuvarthanan Govindaraj
Automated unsupervised learning-based clustering approach for effective anomaly detection in brain magnetic resonance imaging (MRI). IET Image Process. 14(14): 3516-3526 (2020)
2010 – 2019
- 2019
- [j9]Aruna Devi Balasubramanian, Pallikonda Rajasekaran Murugan
Analysis and classification of malignancy in pancreatic magnetic resonance images using neural network techniques. Int. J. Imaging Syst. Technol. 29(4): 399-418 (2019) - [j8]Vigneshwaran Senthilvel
Unsupervised learning-based clustering approach for smart identification of pathologies and segmentation of tissues in brain magnetic resonance imaging. Int. J. Imaging Syst. Technol. 29(4): 439-456 (2019) - 2018
- [j7]P. Rajesh Kumar, Thiyagarajan Arunprasath, Pallikonda Rajasekaran Murugan
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. Comput. Electr. Eng. 72: 283-295 (2018) - [j6]Anitha Vishnuvarthanan
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. Expert Syst. Appl. 95: 280-311 (2018) - 2017
- [j5]Anitha Vishnuvarthanan
An automated hybrid approach using clustering and nature inspired optimization technique for improved tumor and tissue segmentation in magnetic resonance brain images. Appl. Soft Comput. 57: 399-426 (2017) - [j4]Vishnuvarthanan Govindaraj
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. Int. J. Imaging Syst. Technol. 27(1): 33-45 (2017) - [j3]Saravanan Alagarsamy
A fully automated hybrid methodology using Cuckoo-based fuzzy clustering technique for magnetic resonance brain image segmentation. Int. J. Imaging Syst. Technol. 27(4): 317-332 (2017) - 2016
- [c1]Balasubramani Perumal
Efficient Hybrid Approach for Compression of Multi Modal Medical Images. ICTCSDM 2016: 251-261 - 2015
- [j2]Thiyagarajan Arunprasath, Pallikonda Rajasekaran Murugan
ANFIS-EM approach for PET brain image reconstruction. Int. J. Imaging Syst. Technol. 25(1): 1-6 (2015) - 2014
- [j1]Thiyagarajan Arunprasath, Rajasekaran Murugan Pallikonda
PET image reconstruction using ANN. Int. J. Imaging Syst. Technol. 24(3): 249-255 (2014)
Coauthor Index
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