FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3131231694> ?p ?o ?g. }

• W3131231694 endingPage "33322" @default.
• W3131231694 startingPage "33313" @default.
• W3131231694 abstract "The unprecedented improvements in computing capabilities and the introduction of advanced techniques for the analysis, interpretation, processing, and visualization of images have greatly diversified the domain of medical sciences and resulted in the field of medical imaging. The Magnetic Resonance Imaging (MRI), an advanced imaging technique, is capable of producing high quality images of the human body including the brain for diagnosis purposes. This paper proposes a simple but efficient solution for the classification of MRI brain images into normal, and abnormal images containing disorders and injuries. It uses images with brain tumor, acute stroke and alzheimer, besides normal images, from the public dataset developed by harvard medical school, for evaluation purposes. The proposed model is a four step process, in which the steps are named: 1). Pre-processing, 2). Features Extraction, 3). Features Reduction, and 4). Classification. Median filter, being one of the best algorithms, is used for the removal of noise such as salt and pepper, and unwanted components such as scalp and skull, in the pre-processing step. During this stage, the images are converted from gray scale to colored images for further processing. In second step, it uses Discrete Wavelet Transform (DWT) technique to extract different features from the images. In third stage, Color Moments (CMs) are used to reduce the number of features and get an optimal set of characteristics. Images with the optimal set of features are passed to different classifiers for the classification of images. The Feed Forward - ANN (FF-ANN), an individual classifier, which was given a 65% to 35% split ratio for training and testing, and hybrid classifiers called: Random Subspace with Random Forest (RSwithRF) and Random Subspace with Bayesian Network (RSwithBN), which used 10-Fold cross validation technique, resulted in 95.83%, 97.14% and 95.71% accurate classification, in corresponding order. These promising results show that the proposed method is robust and efficient, in comparison with, existing classification methods in terms of accuracy with smaller number of optimal features." @default.
• W3131231694 created "2021-03-01" @default.
• W3131231694 creator A5004287063 @default.
• W3131231694 creator A5021669484 @default.
• W3131231694 creator A5044080887 @default.
• W3131231694 creator A5056975287 @default.
• W3131231694 creator A5073073869 @default.
• W3131231694 creator A5087270783 @default.
• W3131231694 date "2021-01-01" @default.
• W3131231694 modified "2023-10-03" @default.
• W3131231694 title "An Efficient Classification of MRI Brain Images" @default.
• W3131231694 cites W1534477342 @default.
• W3131231694 cites W1578884157 @default.
• W3131231694 cites W1967551258 @default.
• W3131231694 cites W1974314515 @default.
• W3131231694 cites W1978417612 @default.
• W3131231694 cites W1986075844 @default.
• W3131231694 cites W1988819287 @default.
• W3131231694 cites W1993566723 @default.
• W3131231694 cites W1995642009 @default.
• W3131231694 cites W1999286885 @default.
• W3131231694 cites W2017896827 @default.
• W3131231694 cites W2032054866 @default.
• W3131231694 cites W2038344945 @default.
• W3131231694 cites W2047355037 @default.
• W3131231694 cites W2054702571 @default.
• W3131231694 cites W2055957434 @default.
• W3131231694 cites W2063131317 @default.
• W3131231694 cites W2075710390 @default.
• W3131231694 cites W2090221122 @default.
• W3131231694 cites W2090341258 @default.
• W3131231694 cites W2095649164 @default.
• W3131231694 cites W2098765040 @default.
• W3131231694 cites W2131346203 @default.
• W3131231694 cites W2162567222 @default.
• W3131231694 cites W2558107930 @default.
• W3131231694 cites W2718656419 @default.
• W3131231694 cites W2888044560 @default.
• W3131231694 cites W2938518631 @default.
• W3131231694 cites W2947692947 @default.
• W3131231694 cites W2962728585 @default.
• W3131231694 cites W3009718233 @default.
• W3131231694 cites W3011430986 @default.
• W3131231694 cites W3033621327 @default.
• W3131231694 doi "https://doi.org/10.1109/access.2021.3061487" @default.
• W3131231694 hasPublicationYear "2021" @default.
• W3131231694 type Work @default.
• W3131231694 sameAs 3131231694 @default.
• W3131231694 citedByCount "15" @default.
• W3131231694 countsByYear W31312316942022 @default.
• W3131231694 countsByYear W31312316942023 @default.
• W3131231694 crossrefType "journal-article" @default.
• W3131231694 hasAuthorship W3131231694A5004287063 @default.
• W3131231694 hasAuthorship W3131231694A5021669484 @default.
• W3131231694 hasAuthorship W3131231694A5044080887 @default.
• W3131231694 hasAuthorship W3131231694A5056975287 @default.
• W3131231694 hasAuthorship W3131231694A5073073869 @default.
• W3131231694 hasAuthorship W3131231694A5087270783 @default.
• W3131231694 hasBestOaLocation W31312316941 @default.
• W3131231694 hasConcept C115961682 @default.
• W3131231694 hasConcept C153180895 @default.
• W3131231694 hasConcept C154945302 @default.
• W3131231694 hasConcept C160633673 @default.
• W3131231694 hasConcept C196216189 @default.
• W3131231694 hasConcept C31601959 @default.
• W3131231694 hasConcept C31972630 @default.
• W3131231694 hasConcept C36464697 @default.
• W3131231694 hasConcept C41008148 @default.
• W3131231694 hasConcept C46286280 @default.
• W3131231694 hasConcept C47432892 @default.
• W3131231694 hasConcept C52622490 @default.
• W3131231694 hasConcept C78201319 @default.
• W3131231694 hasConcept C9417928 @default.
• W3131231694 hasConceptScore W3131231694C115961682 @default.
• W3131231694 hasConceptScore W3131231694C153180895 @default.
• W3131231694 hasConceptScore W3131231694C154945302 @default.
• W3131231694 hasConceptScore W3131231694C160633673 @default.
• W3131231694 hasConceptScore W3131231694C196216189 @default.
• W3131231694 hasConceptScore W3131231694C31601959 @default.
• W3131231694 hasConceptScore W3131231694C31972630 @default.
• W3131231694 hasConceptScore W3131231694C36464697 @default.
• W3131231694 hasConceptScore W3131231694C41008148 @default.
• W3131231694 hasConceptScore W3131231694C46286280 @default.
• W3131231694 hasConceptScore W3131231694C47432892 @default.
• W3131231694 hasConceptScore W3131231694C52622490 @default.
• W3131231694 hasConceptScore W3131231694C78201319 @default.
• W3131231694 hasConceptScore W3131231694C9417928 @default.
• W3131231694 hasFunder F4320322120 @default.
• W3131231694 hasFunder F4320328359 @default.
• W3131231694 hasFunder F4320335489 @default.
• W3131231694 hasLocation W31312316941 @default.
• W3131231694 hasOpenAccess W3131231694 @default.
• W3131231694 hasPrimaryLocation W31312316941 @default.
• W3131231694 hasRelatedWork W1577789985 @default.
• W3131231694 hasRelatedWork W2014395068 @default.
• W3131231694 hasRelatedWork W2047056993 @default.
• W3131231694 hasRelatedWork W2060518359 @default.
• W3131231694 hasRelatedWork W2075963752 @default.

• next