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A Hybrid Genetic Algorithm based Fuzzy Approach for Abnormal Retinal Image Classification

J. Anitha, C. Kezi Selva Vijila, D. Jude Hemanth
2010 International Journal of Cognitive Informatics and Natural Intelligence  
with the GA optimized fuzzy classifier.  ...  Experimental results suggest highly accurate results for the GA based classifier than the conventional fuzzy classifier.  ... 
doi:10.4018/jcini.2010070103 fatcat:y7swzovdcrfwzjbedp6uiufomq

Automatic semantic segmentation of breast tumors in ultrasound images based on combining fuzzy logic and deep learning-A feasibility study

Samir M Badawy, Abd El-Naser A Mohamed, Alaa A Hefnawy, Hassan E Zidan, Mohammed T GadAllah, Ghada M El-Banby
2021 PLoS ONE  
The proposed batch processing scheme may be generalized for an enhanced CNN based SS of a targeted region of interest (ROI) in any batch of digital images.  ...  In the batch processing mode: quantitative metrics' average results over the eight utilized CNNs based SS models over the 400 cancerous BUS images were: 95.45% GA instead of 86.08% without applying fuzzy  ...  The 400 BUS with tumor images has been enhanced by an FIO based method for contrast enhancement (as been demonstrated in the previous subsections), producing another 400 enhanced images with size 128 by  ... 
doi:10.1371/journal.pone.0251899 pmid:34014987 pmcid:PMC8136850 fatcat:dwzlgcmiuzesdaoix2sr3gxgia

Guest Editorial Special Section on Soft Computing in Industrial Informatics

Xinghuo Yu, Okyay Kaynak, Milos Manic
2012 IEEE Transactions on Industrial Informatics  
Manic is an Associate Editor of the IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, the IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, and several other scholarly journals.  ...  Society, chairing technical committee on resilience and security for industrial applications, and is involved in various capacities in technical committees on education, industrial informatics, factory automation  ...  The paper "Enhancement of Speech Recognitions for Control Automation Using an Intelligent Particle Swarm Optimization," by Chan et al., makes use of Particle Swarm Optimization (PSO) to enhance speech  ... 
doi:10.1109/tii.2012.2215335 fatcat:6huy7iekabfv7pvgp4ywl6toqe

Type2 Fuzzy Soft Computing Technique for Image Enhancement

U. Sesadri, B. Siva Sankar, C. Nagaraju
2015 IAES International Journal of Artificial Intelligence (IJ-AI)  
In the second step based on type1 membership value fuzzy rules are derived to enhance the image. The type2 fuzzy method is compared with type1 fuzzy.  ...  <p class="Default">The mainpurpose of Image enhancement is to process an image so that outcome is more appropriate than original image for definite application.  ...  In [5] , used an erosion enhancement technique by using quality parameters like peak signal to noise ratio (PSNR) and mean square error (MSE) to enhance the gas burner images.  ... 
doi:10.11591/ijai.v4.i3.pp97-104 fatcat:op4vv5cv3vaihfkjnfsmgo5him

Computerised Retinal Image Analysis to Detect and Quantify Exudates Associated with Diabetic Retinopathy

M. PonniBala, S. Vijayachitra
2012 International Journal of Computer Applications  
Finally, an automated Fuzzy Inference System (FIS) is used for classifying the retinal images as exudates and its severity and non-exudates.  ...  As this method takes time and energy of the ophthalmogists, a new feature based automated technique for classification and detection of exudates in color fundus image is proposed in this paper.  ...  The authors are grateful to Lotus Eye Care Hospital, Coimbatore for providing the photographic database of eye images and also to Dr. R. J. Madhusudanan DO, for his valuable suggestions on this work.  ... 
doi:10.5120/8536-2077 fatcat:yplf35ekszbknhqsvmu57fnytq

Brain Tumor Segmentation using Genetic Algorithm and FCM Clustering Approach

Garima Garg, Sonia Juneja
2012 International Journal of Computer Applications  
Image processing is any type of signal processing in which we take any abnormal image of brain tumor and then produce an output which is extracted portion of tumor by applying genetic algorithm with fuzzy  ...  clustering means method.  ...  Genetic Algorithms (GAs) was invented by John Holland. Holland proposed GA as a heuristic method based on "Survival of the fittest".  ... 
doi:10.5120/7601-0331 fatcat:fuz7oa6rvfg4lbhgkjcseis3pe

Enriched Fuzzy and L*A*B based Mix Contrast Limited Adaptive Histogram Equilization

Kanika Sharma, Navneet Bawa, Ajay Sharma
2015 International Journal of Computer Applications  
This paper has proposed an hybrid approach which includes integrated the MIX-CLAHE with the L*A*B based fuzzy enhancement.  ...  In this paper a novel algorithm has been designed to get rid of the problem of over-enhancement found in Mix CLAHE specifically for underwater images.  ...  This paper has offered an hybrid approach that has integrated the MIX-CLAHE with the L*A*B based fuzzy enhancement.  ... 
doi:10.5120/20122-2190 fatcat:pzklv2s63fe6dby33h2ztgosmu

Biomedical Image Segmentation using Optimized Fuzzy C-mean Algorithm

Sarojlaxmi Jena, Mohan Debarchan Mohanty, Mihir Narayan Mohanty
2017 Indian Journal of Science and Technology  
Both the concept of clustering by fuzzy technique with edge based segmentation method where standard methods like Sobel, Prewitt edge detectors are applied.  ...  Background/Objectives: Automatic segmentation of brain MRI has an important role in image research along with medical image processing. It has been investigated widely in recent research.  ...  The objective of this work is use the GFCM method to optimize the image segmentation. We have analysed the work using the popular fuzzy based clustering approach.  ... 
doi:10.17485/ijst/2017/v10i35/118948 fatcat:degxwgfb4vcmnkd2u4x4iinbra

Towards Better Segmentation of Abnormal Part in Multimodal Images Using Kernel Possibilistic C Means Particle Swarm Optimization With Morphological Reconstruction Filters

Sumathi R., Venkatesulu Mandadi
2021 International Journal of E-Health and Medical Communications (IJEHMC)  
The authors designed an automated framework to segment tumors with various image sequences like T1, T2, and post-processed MRI multimodal images.  ...  Contrast-limited adaptive histogram equalization method is used for preprocessing images to enhance the intensity level and view the tumor part clearly.  ...  To overcome the above said issues, an automated segmentation is required.  ... 
doi:10.4018/ijehmc.20210501.oa4 fatcat:p4empiixnjcnxkqzhvvqmmudqe

A Review On Automatic Detection of Brain Tumor Using Computer Aided Diagnosis System Through MRI

Meera R, Dr. Anandhan, P
2018 EAI Endorsed Transactions on Energy Web  
Xiao et al analyses the images from MRI using Statistical Structure Analysis also known as an automated method [42] .  ...  detection is enhancing, if GA is applied.  ... 
doi:10.4108/eai.12-9-2018.155747 fatcat:4xnmrtl4mjdljo67v3arbdnfrm

Designing a New Framework Using Type-2 FLS and Cooperative-Competitive Genetic Algorithms for Road Detection from IKONOS Satellite Imagery

Maryam Nikfar, Mohammad Zoej, Mehdi Mokhtarzade, Mahdi Shoorehdeli
2015 Remote Sensing  
Doucette et al. presented an automated road centerline extraction method that exploits spectral content from high-resolution multi-spectral images [8] .  ...  To reduce the effects of vagueness in road detection from satellite images, T1 FSs have been proposed in some literature. Agouris et al. used fuzzy logic for segmentation of an image.  ...  Singh and Garg proposed a weighted membership function-based fuzzy c-means with spatial constraints approach for automated road extraction.  ... 
doi:10.3390/rs70708271 fatcat:efakvynimfcgfprxzayg4ghzl4

A Review on Segmentation Techniques in Large-Scale Remote Sensing Images

Rakesh Tripathi, Neelesh Gupta
Image segmentation is an important processing step in most image, video and computer vision applications.  ...  Various algorithms for automating the segmentation process have been proposed, tested and evaluated to find the most ideal algorithm to be used for different types of images.  ...  Methods Based on Fuzzy Set Theory Application of fuzzy sets [20] to image processing was based on the realization that many of the basic concepts in image analysis, e.g., the concept of an edge or a  ... 
doi:10.24113/ijoscience.v4i4.143 fatcat:zjljxjopn5cdjdualrcwhf4h7m

Special issue on intelligent tools and techniques for signals, machines and automation

Smriti Srivastava, Hasmat Malik, Rajneesh Sharma
2018 Journal of Intelligent & Fuzzy Systems  
In [12] , an Adaptive Neuro Fuzzy Inference System (ANFIS) is used to enhance the performance of UPFC. The performance is compared to both conventional control schemes as well as a fuzzy controller.  ...  In [26] , a PI and Fuzzy based technique is used to improve the efficiency of vector control of an induction motor drive system.  ... 
doi:10.3233/jifs-169773 fatcat:gjntjnlig5fabdbqlwsjpl2awm


2019 Zenodo  
This paper provides a detailed analysis of the existent methods and approaches utilized in medical image segmentation.  ...  Additionally, the paper will provide an analysis of the process integrated pertaining to the retrieval of brain images through the identification of the specific data sets selected in the process to identify  ...  like Genetic Algorithm (GA), k-means, and Fuzzy C-Means (FCM).  ... 
doi:10.5281/zenodo.3256441 fatcat:xiqd75juvbbhnjbwffgruujnbi

Incorporating priors for medical image segmentation using a genetic algorithm

Payel Ghosh, Melanie Mitchell, James A. Tanyi, Arthur Y. Hung
2016 Neurocomputing  
Automating the process is challenging due to poor tissue contrast and ill-defined organ/tissue boundaries in medical images.  ...  The algorithm has been tested for prostate segmentation on pelvic computed tomography and magnetic resonance images.  ...  The GA optimized an energy function based on features such as smoothness of the curve, curvature and image gradient.  ... 
doi:10.1016/j.neucom.2015.09.123 fatcat:ucnuoptamfa2hl2awt3n6un2qa
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