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Review Paper of Image processing technique for the diagnosis of diseases
2018
International Journal of Trend in Scientific Research and Development
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In recent times, image processing techniques are used in medical field for image improvement in earlier detection of diseases, Medical informatics is the study that combines two medical data sources: biomedical ...
be feasible working for computer-aided-diagnosis are a big challenge. ...
Fuzzy logic is an branch of Boolean logic by Lot_ Zadeh in 1965 based on the mathematical theory of fuzzy sets, which is a simplification of the classical set theory. ...
doi:10.31142/ijtsrd10703
fatcat:khdx2pm2s5holezyv44xrsqd2e
Content-Based Retrieval Of Medical Images
2012
Zenodo
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This paper presents an ongoing research that focuses on the semantic content of radiographic image documents to facilitate semantic-based radiographic image indexing and a retrieval system. ...
The proposed model would divide a radiographic image document, based on its semantic content, and would be converted into a logical structure or a semantic structure. ...
The semantic interpretation of medical images needs knowledge bases. The following example that describes how our proposed system intent to interpret radiographic images: A physician enters an x-ray. ...
doi:10.5281/zenodo.1082997
fatcat:75ojihsryzf3npeuw3gbn7l5by
Hybrid intelligent diagnosis approach based on soft computing from signal and image knowledge representations for a biomedical application
2014
Vietnam Journal of Computer Science
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Afterwards, a hybrid intelligent diagnosis approach, based on soft computing implying modular neural networks for classification and fuzzy logic for decision-making, is suggested from signal and image ...
Fault diagnosis is a complex and fuzzy cognitive process, and soft computing methods as neural networks and fuzzy logic, have shown great potential in the development of decision support systems. ...
The fuzzy decisionmaking system based on a fuzzy inference can be exploited in order to capture the expert (human) knowledge [2, 20] . ...
doi:10.1007/s40595-014-0017-6
fatcat:wc6u7tef4ffrvgtbn2fstgh2pu
Artificial Intelligence in Bio-Medical Domain
2017
International Journal of Advanced Computer Science and Applications
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We hope, this work will be helpful for the researchers coming to this particular area and to provide a syntactic information that how computer science (i.e. ...
AI, ANN, ML) is revolutionizing the field of biomedical and healthcare. ...
And these fuzzy sets are said to be ‗rulebase' or knowledge base of a fuzzy expert system.
V. ...
doi:10.14569/ijacsa.2017.080842
fatcat:p7wurhzxwbd3vhcixkity2y5iq
VISUAL AND COGNITIVE INTERPRETATION OF HETEROGENEOUS DATA
2019
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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An example application of this technology for processing biomedical data is considered.</p> ...
Development and practical application of visualization tools allow to overcome these factors as a result of using the advantages of visual perception for the source data interpretation. ...
There is a whole class of cognitive models based on different types of fuzzy cognitive maps (FCMs). ...
doi:10.5194/isprs-archives-xlii-2-w12-243-2019
fatcat:v4zoq23t6faalcdjjfefdjjxyy
Rough sets and fuzzy sets in natural computing
2011
Theoretical Computer Science
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Rough sets and fuzzy sets in natural computing Natural Computing (NC) is a discipline that builds a bridge between computer science and natural sciences. ...
The structure of granulation can often be defined using methods based on rough sets, fuzzy sets or their combination. ...
The paper ''Fuzzy Quartile Encoding as a Preprocessing Method for Biomedical Pattern Classification'', by Nick J. ...
doi:10.1016/j.tcs.2011.05.036
fatcat:ptgtfw6wrncz7nqm6rci6p4lrm
Survey Paper on Clustering based Segmentation Approach to Detect Brain Tumour from MRI Scan
2015
International Journal of Computer Applications
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These cover Content-Based Retrieval Technique, Component Labelling Algorithm, Fuzzy C-Mean Algorithm. ...
With this survey paper we focus on literature survey of segmentation based image processing model as contain efficient performance. ...
Computer Aided System In this paper they propose a method for automatic brain tumor diagnostic system from MRI images. The system consists of three steps to detect and segment a brain tumor [13] . ...
doi:10.5120/20219-2498
fatcat:33f3gycymnbd7p46bomq376kze
Fluorescence Pattern Analysis-How To Achieve a Better Quality-Standard?
2017
Current Trends in Biomedical Engineering & Biosciences
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and multi tracking laser control systems. ...
These microscopic images can be of 2-dimensional or 3-dimensional nature, or even 4-dimensional nature such as videos recording the life cycle of a cell. ...
As a result, ontologies were born for specific image interpretation tasks. The ontology is the basis for the development of an automatically image-interpretation-systems. ...
doi:10.19080/ctbeb.2017.09.555769
fatcat:qfvlwg32gbbj7m5fpvmsd35fmi
A Survey on Neural Network based Automatic Segmentation of Brain Magnetic Resonance Images
English
2015
International Journal of Research and Applications
English
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Especially, image segmentation is a prerequisite process for image content understanding in brain MRI for the development of a computer aided diagnosis (CAD) system. ...
The review covers imaging techniques, magnetic resonance imaging and methods for segmentation and how a known Neural Network with fixed structure and training procedure could be applied to resolve medical ...
A number of approaches to segmentation of head or brain images have been presented in past years: pattern recognition techniques, rule based systems, and knowledge-based approach are some of them. ...
doi:10.17812/ijra.2.7(60)2015
fatcat:fjjehiso35dwjdihcq6nncmcdy
An Approach to Brain Tumor MR Image Detection and Classification using Neuro Fuzzy
2013
Jurnal Teknologi
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Hence, in this study, the neuro fuzzy system or ANFIS is applied for classification purposes. ANFIS is applied to classify the abnormal brain based on the location of the tumors. ...
Thresholding is one of the most important and used techniques for image segmentation. Some segmentation techniques based on thresholding are performed in order to segment the tumors. ...
Acknowledgement This paper is a part of a publication series on Research and Development in Signal, Image and Sensors in Biomedical Engineering Applications. ...
doi:10.11113/jt.v61.1627
fatcat:2ffu53i27ff4hmcyjm5japeoay
Comparison of Fuzzy Contrast Enhancement Techniques
2014
International Journal of Computer Applications
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In first technique fuzzy system response function is obtained by simple if-then rules, and in second technique the fuzzy contrast intensification operator is taken as a tool for the enhancement in the ...
The aim of the image enhancement is to improve the interpretability or perception of the information in images for human viewers, or to provide 'better' input for other automated image processing techniques ...
Illustration of two algorithms for Rose image, a) Original image, b) output of fuzzy rule based method, c) output of fuzzy INT operator method, d) histogram of (a), e) histogram of (b), f) histogram of ...
doi:10.5120/16728-6986
fatcat:qt7vlsm2ijf77n7oqtm5gshixa
Edge Detection with Neuro-Fuzzy Approach in Digital Synthesis Images
2016
International Journal of Advanced Computer Science and Applications
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The original inspired NF edge detection model uses just one image learning database realized by Emin Yuksel. The tests are accomplished in synthesis images with a noised one of 20% of Gaussian noise. ...
This paper presents an enhanced Neuro-Fuzzy (NF) Approach of edge detection with an analysis of the characteristic of the method. ...
Neuro-Fuzzy system based in Takagi-Sugeno fuzzy inference system was used in [12] as a classifier for image retrieval. They use Canny detector for the learning database.
II. ...
doi:10.14569/ijacsa.2016.070448
fatcat:dowshj4u75attc7j2psfxzhleu
Images, morphology and metaphors in biomedical research
2017
Azafea: Revista de Filosofía
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Some of the key discoveries of the last two centuries of biomedical research can be represented through a sequence of influential images that were originally powerful metaphors. ...
Metaphor, as a model of proposition that includes the two extreme types of diaphor and epiphor, can serve the purpose of representing knowledge in a dynamic way. ...
A metaphorical theory of knowledge In his first conception of language Wittgenstein suggested an interpretation of the proposition as a "measurement tool": the only true knowledge is scientific knowledge ...
doaj:f8b4b59091ff4b92ba3ce379b0547496
fatcat:l3iyxbfuane45ljo627mjbonbe
Soft Computing for Analysis of Biomedical Data
2018
Computational and Mathematical Methods in Medicine
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Acknowledgments e editors would like to thank all authors who submitted their research to this special issue, as well as all reviewers for their valuable contribution. ...
Such a method performs a pruning of irrelevant information in the input network to facilitate the interpretation of the biological knowledge that comprises the network. ...
For this reason, SC techniques can obtain approximate solutions to problems which have no known methods to compute an exact solution. e main SC paradigms include fuzzy systems, evolutionary computation ...
doi:10.1155/2018/3902484
fatcat:yfkcr4jjj5fzfgbcmgrocy3e2y
GRAFIP: A FRAMEWORK FOR THE REPRESENTATION OF HEALTHY AND PATHOLOGICAL CEREBRAL INFORMATION
2007
2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro
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In this paper we describe a novel generic brain model, based on graph representations, and an instantiation procedure for individual patients, based on image segmentation. ...
This paper presents a contribution to the large problematic of integrating medical image-based information into a structured framework (such as electronic patient records or anatomofunctional databases ...
Knowledge-based image interpretation systems, reviewed in [2] , have been successfully applied to drive specific recog-This work has been partly founded by GET nition procedures, as in [3, 4] for ...
doi:10.1109/isbi.2007.356824
dblp:conf/isbi/AtifHNRBAB07
fatcat:oenh3rsamrcebkn2pk5di6scge
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