An improved support vector machine kernel for medical image retrieval system

Kumar, Mukesh; Kumaraswamy, Y. S.

doi:10.1109/icprime.2012.6208354

Cited by 6 publications

(2 citation statements)

References 13 publications

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“…In this case, big energy value shows that image texture is coarse. Energy can be computed according to formula (8).…”

Section: Energymentioning

confidence: 99%

“…When features have been selected, image retrieval needs good methods to classify these features in order to obtain the best result similar to query image [7]. Support vector machine is in common use for retrieval in medical image database including X-Rays, MRI, and CT. IRMA is an efficient image retrieval system using feature fusion and support vector machine [8].…”

Section: Introductionmentioning

confidence: 99%

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

Liu

Chen

et al. 2019

Computer Assisted Surgery

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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 order to increase the credibility of the retrieval process, many features can be combined to be used for medical image retrieval. Meanwhile, more features require more processing time, which will decrease the retrieval speed. 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. Experimental results show that the proposed multi-feature fusion method can achieve a higher retrieval accuracy with an acceptable retrieval time. KEYWORDSWord; medical image retrieval; bag-of-feature; texture feature; LBP feature CONTACT Pang Ming

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“…In this case, big energy value shows that image texture is coarse. Energy can be computed according to formula (8).…”

Section: Energymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%