Evaluation of brain tumor using brain MRI with modified-moth-flame algorithm and Kapur’s thresholding: a study

[1]  Mariella Scerri,et al.  Artificial Intelligence in Medicine: 18th International Conference on Artificial Intelligence in Medicine, AIME 2020, Minneapolis, MN, USA, August 25–28, 2020, Proceedings , 2020, The Bible of AI ™.

[2]  Ganesh Naik,et al.  A supervised blood vessel segmentation technique for digital Fundus images using Zernike Moment based features , 2020, PloS one.

[3]  V. Rajinikanth,et al.  Evaluation and Classification of the Brain Tumor MRI using Machine Learning Technique , 2019 .

[4]  Alex Noel Joseph Raj,et al.  A fuzzy clustering based color-coded diagram for effective illustration of blood perfusion parameters in contrast-enhanced ultrasound videos , 2019, Comput. Methods Programs Biomed..

[5]  Hojjat Adeli,et al.  Artificial Intelligence Techniques for Automated Diagnosis of Neurological Disorders , 2019, European Neurology.

[6]  U. Rajendra Acharya,et al.  Convolutional neural networks for multi-class brain disease detection using MRI images , 2019, Comput. Medical Imaging Graph..

[7]  Mohd Kamil Bin Mohd Fabell,et al.  Automated Detection of Alzheimer’s Disease Using Brain MRI Images– A Study with Various Feature Extraction Techniques , 2019, Journal of Medical Systems.

[8]  V. Rajinikanth,et al.  A reliable framework for accurate brain image examination and treatment planning based on early diagnosis support for clinicians , 2019, Neural Computing and Applications.

[9]  V. Rajinikanth,et al.  Social-Group-Optimization based tumor evaluation tool for clinical brain MRI of Flair/diffusion-weighted modality , 2019, Biocybernetics and Biomedical Engineering.

[10]  U. Rajendra Acharya,et al.  Automatic detection of ischemic stroke using higher order spectra features in brain MRI images , 2019, Cognitive Systems Research.

[11]  Alex Noel Joseph Raj,et al.  A Multi-Sensor System for Silkworm Cocoon Gender Classification via Image Processing and Support Vector Machine , 2019, Sensors.

[12]  Heming Jia,et al.  Multilevel Thresholding Segmentation for Color Image Using Modified Moth-Flame Optimization , 2019, IEEE Access.

[13]  Venkatesan Rajinikanth,et al.  Jaya Algorithm Guided Procedure to Segment Tumor from Brain MRI , 2018, Journal of Optimization.

[14]  P. V. Krishna,et al.  Internet of Things and Personalized Healthcare Systems , 2018, SpringerBriefs in Applied Sciences and Technology.

[15]  Muhammad Sharif,et al.  Big data analysis for brain tumor detection: Deep convolutional neural networks , 2018, Future Gener. Comput. Syst..

[16]  V. Rajinikanth,et al.  An Approach to Examine Brain Tumor Based on Kapur’s Entropy and Chan–Vese Algorithm , 2018, Advances in Intelligent Systems and Computing.

[17]  Manjeet Singh,et al.  A fuzzy-based automatic prediction system for quality evaluation of conceptual data warehouse models , 2018, Int. J. Data Anal. Tech. Strateg..

[18]  Nilanjan Dey,et al.  An approach to examine Magnetic Resonance Angiography based on Tsallis entropy and deformable snake model , 2018, Future Gener. Comput. Syst..

[19]  V. Rajinikanth,et al.  Computational Investigation of Stroke Lesion Segmentation from Flair/DW Modality MRI , 2018, 2018 Fourth International Conference on Biosignals, Images and Instrumentation (ICBSII).

[20]  P. Marikkannu,et al.  MRI Brain Images Classification: A Multi-Level Threshold Based Region Optimization Technique , 2018, Journal of Medical Systems.

[21]  Gongning Luo,et al.  Concatenated and Connected Random Forests With Multiscale Patch Driven Active Contour Model for Automated Brain Tumor Segmentation of MR Images , 2018, IEEE Transactions on Medical Imaging.

[22]  D. Shen,et al.  Anatomical Landmark Based Deep Feature Representation for MR Images in Brain Disease Diagnosis , 2018, IEEE Journal of Biomedical and Health Informatics.

[23]  Aboul Ella Hassanien,et al.  Whale Optimization Algorithm and Moth-Flame Optimization for multilevel thresholding image segmentation , 2017, Expert Syst. Appl..

[24]  N. Sri Madhava Raja,et al.  Firefly Algorithm Assisted Segmentation of Tumor from Brain MRI using Tsallis Function and Markov Random Field , 2017 .

[25]  V. Rajinikanth,et al.  Entropy based segmentation of tumor from brain MR images - a study with teaching learning based optimization , 2017, Pattern Recognit. Lett..

[26]  Ahmad Taher Azar,et al.  Fuzzy firefly clustering for tumour and cancer analysis , 2017, Int. J. Model. Identif. Control..

[27]  Nilesh Bhaskarrao Bahadure,et al.  Image Analysis for MRI Based Brain Tumor Detection and Feature Extraction Using Biologically Inspired BWT and SVM , 2017, Int. J. Biomed. Imaging.

[28]  Nilanjan Dey,et al.  Multi-level image thresholding using Otsu and chaotic bat algorithm , 2016, Neural Computing and Applications.

[29]  Ahmad Taher Azar,et al.  Tolerance rough set firefly-based quick reduct , 2016, Neural Computing and Applications.

[30]  G. Reifenberger,et al.  The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary , 2016, Acta Neuropathologica.

[31]  Parvathavarthini Balasubramanian,et al.  Segmentation of Brain Regions by Integrating Meta Heuristic Multilevel Threshold with Markov Random Field , 2016 .

[32]  Seyed Mohammad Mirjalili,et al.  Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm , 2015, Knowl. Based Syst..

[33]  Brian B. Avants,et al.  The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) , 2015, IEEE Transactions on Medical Imaging.

[34]  Christopher Joseph Pal,et al.  Brain tumor segmentation with Deep Neural Networks , 2015, Medical Image Anal..

[35]  Kenneth Revett,et al.  Computer-aided diagnosis of human brain tumor through MRI: A survey and a new algorithm , 2014, Expert Syst. Appl..

[36]  Aboul Ella Hassanien,et al.  A Hybrid Approach to Diagnosis of Hepatic Tumors in Computed Tomography Images , 2014, Int. J. Rough Sets Data Anal..

[37]  Stephen M. Moore,et al.  The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository , 2013, Journal of Digital Imaging.

[38]  S. Bauer,et al.  A survey of MRI-based medical image analysis for brain tumor studies , 2013, Physics in medicine and biology.

[39]  Guido Gerig,et al.  User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability , 2006, NeuroImage.

[40]  Nilanjan Dey,et al.  Internet of Things and Its Impacts in Computing Intelligence , 2019, Advances in Civil and Industrial Engineering.

[41]  V. Rajinikanth,et al.  Segmentation of Tumor from Brain MRI Using Fuzzy Entropy and Distance Regularised Level Set , 2018 .

[42]  Hong Lin,et al.  Evaluation of Ischemic Stroke Region From CT/MR Images Using Hybrid Image Processing Techniques , 2018 .

[43]  Naveen Dahiya,et al.  A Classification Framework Towards Application of Data Mining in Collaborative Filtering , 2017 .

[44]  Ahmad Taher Azar,et al.  Hybrid Bijective soft set - Neural network for ECG arrhythmia classification , 2015, Int. J. Hybrid Intell. Syst..

[45]  Ahmad Taher Azar,et al.  Classification of EEG-Based Brain-Computer Interfaces , 2014, Advanced Intelligent Computational Technologies and Decision Support Systems.

[46]  V. Rajinikanth,et al.  Otsu based optimal multilevel image thresholding using firefly algorithm , 2014 .

[47]  Hilde van der Togt,et al.  Publisher's Note , 2003, J. Netw. Comput. Appl..