Vishnuvarthanan Govindaraj

Orcid: 0000-0001-9136-3461

According to our database1, Vishnuvarthanan Govindaraj authored at least 24 papers between 2014 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Bibliography

2023
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., December, 2023

Automated Brain Tumor Segmentation for MR Brain Images Using Artificial Bee Colony Combined With Interval Type-II Fuzzy Technique.
IEEE Trans. Ind. Informatics, November, 2023

Development of scalable coding on encrypted images using BTC for different non-overlapping block size.
Signal Image Video Process., October, 2023

Development of scalable coding for the encryption and decryption of images using modified diagonal min-max block truncation code.
Multim. Tools Appl., March, 2023

2022
A novel triple-level combinational framework for brain anomaly segmentation to augment clinical diagnosis.
Comput. methods Biomech. Biomed. Eng. Imaging Vis., 2022

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., 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.
Biomed. Signal Process. Control., 2022

Minimally parametrized segmentation framework with dual metaheuristic optimisation algorithms and FCM for detection of anomalies in MR brain images.
Biomed. Signal Process. Control., 2022

2021
Smart Identification of Topographically Variant Anomalies in Brain Magnetic Resonance Imaging Using a Fish School-Based Fuzzy Clustering Approach.
IEEE Trans. Fuzzy Syst., 2021

Covid-19 classification by FGCNet with deep feature fusion from graph convolutional network and convolutional neural network.
Inf. Fusion, 2021

A smartly designed automated map based clustering algorithm for the enhanced diagnosis of pathologies in brain MR images.
Expert Syst. J. Knowl. Eng., 2021

2020
Hearing loss detection by discrete wavelet transform and multi-layer perceptron trained by nature-inspired algorithms.
Multim. Tools Appl., 2020

Automated unsupervised learning-based clustering approach for effective anomaly detection in brain magnetic resonance imaging (MRI).
IET Image Process., 2020

2019
High Performance Multiple Sclerosis Classification by Data Augmentation and AlexNet Transfer Learning Model.
J. Medical Imaging Health Informatics, 2019

Unsupervised learning-based clustering approach for smart identification of pathologies and segmentation of tissues in brain magnetic resonance imaging.
Int. J. Imaging Syst. Technol., 2019

2018
Smart pathological brain detection by synthetic minority oversampling technique, extreme learning machine, and Jaya algorithm.
Multim. Tools Appl., 2018

Ridge-based curvilinear structure detection for identifying road in remote sensing image and backbone in neuron dendrite image.
Multim. Tools Appl., 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.
Expert Syst. Appl., 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.
Comput. Electr. Eng., 2018

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.
Int. J. Imaging Syst. Technol., 2017

A fully automated hybrid methodology using Cuckoo-based fuzzy clustering technique for magnetic resonance brain image segmentation.
Int. J. Imaging Syst. Technol., 2017

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., 2017

2016
An unsupervised learning method with a clustering approach for tumor identification and tissue segmentation in magnetic resonance brain images.
Appl. Soft Comput., 2016

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.
Int. J. Imaging Syst. Technol., 2014


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