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Erschienen in:
2019 | OriginalPaper | Buchkapitel
Analysis of Feature Ranking Methods on X-Ray Images
verfasst von : H. Roopa, T. Asha
Erschienen in: Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB)
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Abstract
Mycobacterium causes an infectious disease called tuberculosis which can be diagnosed by its various symptoms like fever, cough, etc. Tuberculosis can also be analyzed by understanding the chest X-ray of the patient which is revealed by an expert physician. The chest X-ray image contains texture and shape-based features which are extracted from X-ray image using image processing concepts. This paper presents implementation of various feature weighting methods on the extracted features of X-ray images. These feature weighting methods are analyzed using linear regression model and Linear Discriminant Analysis (LDA) model. The performance of various feature weighting methods is compared and found that the accuracy of weights by PCA using linear regression model is 98.75% which is better than other methods.