Automatic retrival of MRI brain image using multiqueries system

Mohanapriya, S.; Vadivel, M.

doi:10.1109/icices.2013.6508214

Cited by 13 publications

(5 citation statements)

References 6 publications

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“…His Algorithm is based on classification [22] using a majority vote of its neighbors, with the case being assigned to the class most common amongst its K nearest neighbors measured by a Euclidean Distance.…”

Section: Knn (K_ Nearest _neighbors)mentioning

confidence: 99%

An Effective System for Content MRI Brain Image Retrieval using Angular Radial Transform

Khatabi¹,

Tmiri²,

Serhir³

2015

IJCA

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Nowadays, the growth of huge amount of medical image has become one of the most important clinical diagnosis components, Furthermore, there is an urgent need a system of Content Based Image Retrieval (CBIR) to obtain essential information such as type of image and extracting features of the image, such as color, shape and texture. This system is based on the image content that retrieves similar pathology involving magnetic resonance (MR) images of the medical database to assist the radiologist in the diagnosis of brain tumor; the shape recovery is the one of the top performers. Content-based image retrieval can also be used to locate brain tumors in medical images in large databases. In this paper, we propose a new method to build a new research system by the content of MRI images (CBIR) based on image characteristics, such as shape using the ART descriptor (angular radial transform) that is applied to reveal the characteristics of MR images. ART descriptor (angular radial transform) of shape is based Region adopted in MPEG-7 has the properties invariant to scale, rotation and robustness to noise, thanks to its properties we have used in this system. After the segmentation process, extracting the visual features of shape by calculating the coefficients of the ART and forming a second feature vector to be input to a support vector machine (SVM) for determining the presence tumor or not tumor followed by KNN (K-nearest neighbor) that retrieves the most similar images in the database. To provide faster image search. General TermsContent based image retrieval; Classification; KeywordsART descriptor (angular radial transform), Content based image retrieval (CBIR), magnetic resonance (MR) images, feature extraction, SVM, KNN.

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Section: Knn (K_ Nearest _neighbors)mentioning

confidence: 99%

An Effective System for Content MRI Brain Image Retrieval using Angular Radial Transform

Khatabi¹,

Tmiri²,

Serhir³

2015

IJCA

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“…It is necessary to adjust the amount of a product in your basket when you add it to your cart from another location. The summary must be updated as soon as any alterations to the goods are made to the cart's contents [ 16 ].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Encryption Method for Health Monitoring Systems Based on Machine Learning

Malmurugan

Nelson

Altuwairiqi

et al. 2022

Computational Intelligence and Neuroscience

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Numerous forms of disasters and vandalism can occur in transmission lines, which makes them vulnerable. As a result, the transmission pipes must be protected by a reliable monitoring system. When a wireless sensor network is built from disparate devices that are positioned at varying distances from one another, it can be used to monitor physical and environmental conditions in the surrounding environment. In addition to the built-in sensor on the exterior of a pipeline and sensors positioned to support bridge structures, wireless sensor networks have a range of other applications. Other uses include robotics, healthcare, environmental monitoring, and a variety of other areas of technology. It is feasible to use wireless sensor networks to monitor temperature and pressure, as well as leak detection and transmission line sabotage, among other applications. There are several different sorts of attacks that can be launched against wireless sensor networks. When it comes to information security in wireless sensor networks, cryptographic approaches play a critical role in ensuring the integrity of the data. Different types of cryptographic algorithms are now available for use in order to maintain network security. Specific difficulties must be addressed, though, and these are as follows: To strengthen the power of these algorithms, a unique hybrid encryption approach for monitoring energy transmission lines and increasing the security of wireless sensor networks is created in this study. While wireless sensor networks are being used to monitor transmission pipelines, the proposed hybrid encryption method ensures that data is transferred securely and promptly. The proposed method must follow three cryptographic principles: integrity, secrecy, and authenticity. All of the subtleties and underlying principles of the algorithm are explained in detail so that the algorithm can be put into action immediately after it is introduced.

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“…Mohanapriya.S [5],this paper introduce a novel method of using SVM classifier followed by KNN for CBIR using shape feature and texture feature of MRI brain image. The Gray level cooccurance matrix are used to extract texture feature of images.…”

Section: Literature Surveymentioning

confidence: 99%

Two Tier Approach for Automatic Retrieval of MRI Brain Image by Feature Extraction

Chavan¹,

Gore²

2015

IJCA

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Automatic retrival of MRI brain image using multiqueries system

Cited by 13 publications

References 6 publications

An Effective System for Content MRI Brain Image Retrieval using Angular Radial Transform

An Effective System for Content MRI Brain Image Retrieval using Angular Radial Transform

Hybrid Encryption Method for Health Monitoring Systems Based on Machine Learning

Two Tier Approach for Automatic Retrieval of MRI Brain Image by Feature Extraction

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