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| Neural Network Based Classification and Diagnosis of Brain Hemorrhages
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Full
text: |
 PDF(2.17MB) |
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Source |
International Journal of Artificial Intelligence and Expert Systems (IJAE) |
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Table of Contents |
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Download
Complete Issue PDF(3.2MB) |
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Volume: 1 Issue: 2 |
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Pages: 7-53 |
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Publication
Date: July 2010 |
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ISSN
(Online): 2180-124X |
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Pages |
7 - 25 |
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Author(s) |
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Published
Date |
10-06-2010 |
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Publisher |
CSC
Journals, Kuala Lumpur,
Malaysia |
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ADDITIONAL
INFORMATION |
| Keywords Abstract References Cited by Related Articles Collaborative
Colleague |
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KEYWORDS: Brain hemorrhages, CAD system, Region Severance Algorithm |
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| 3. Docstoc |
| 4. Directory of Open Access Journals (DOAJ) |
| 5. Google Scholar |
| 6. Academic Index |
| 7. refSeek |
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| The classification and diagnosis of brain hemorrhages has work out into a great importance diligence in early detection of hemorrhages which reduce the death rates. The purpose of this research was to detect brain hemorrhages and classify them and provide the patient with correct diagnosis. A possible solution to this social problem is to utilize predictive techniques such as sparse component analysis, artificial neural networks to develop a method for detection and classification. In this study we considered a perceptron based feed forward neural network for early detection of hemorrhages. This paper attempts to spot on consider and talk about Computer Aided Diagnosis (CAD) that chiefly necessitated in clinical diagnosis without human act. This paper introduces a Region Severance Algorithm (RSA) for detection and location of hemorrhages and an algorithm for finding threshold band. In this paper different data sets (CT images) are taken from various machines and the results obtained by applying our algorithm and those results were compared with domain expert. Further researches were challenged to originate different models in study of hemorrhages caused by hyper tension or by existing tumor in the brain. |
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| K.V.Ramana M.Tech : Colleagues
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| Raghu Korrpati : Colleagues
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