Multi-feature fusion method for medical image retrieval using wavelet and bag-of-features

6,000.00

Multi-feature fusion method for medical image retrieval using wavelet and bag-of-features

100 in stock

SKU: Multi-feature fusion method for medical image retrieval using Category:

Description

Multi-feature fusion method for medical image retrieval using wavelet and bag-of-features

  The accuracy of Medical image retrieval using wavelet and bag-of-features based on deep learning is much higher than that of image fusion algorithm.

Color, texture, and shape are the common features used for the retrieval systems. However, many medical images have a spot of color information. Therefore, the discriminative texture and shape features should be extracted to obtain a satisfied retrieval result. In this paper, wavelet decomposition is adopted to generate different resolution images. Bag-of-feature, texture, and LBP feature are extracted from three different-level wavelet images. Finally, the similarity measure function is obtained by fusing these three types of features.Cardiac CT images are important parts of the medical database, and related retrieval methods have been formed by taking advantage of the heart shape. A contour and texture based image retrieval technology has been put forward and applied to the liver image database.The proposed method is retrieval framework of the images.

Experimental results show that the proposed multi-feature fusion method can achieve a higher retrieval accuracy with an acceptable retrieval time.

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Weight 1.000000 kg

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