A New Fracture Image Segmentation Method Based on MSA-k Clustering Algorithm

Deng, Liwei; Wang, Xiaofei; Ai, Ling

doi:10.23919/ccc50068.2020.9188496

Cited by 1 publication

(1 citation statement)

References 16 publications

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“…The MSA-K algorithm is a quickly convergent version of the clustering algorithm proposed by Liwei at the 39th CCC International Conference. The steps of the MSA-K algorithm are as follows [36]:…”

Section: Msa-k Algorithmmentioning

confidence: 99%

Multifeature Detection of Microaneurysms Based on Improved SSA

Deng

Wang

2021

Symmetry

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The early diagnosis of retinopathy is crucial to the prevention and treatment of diabetic retinopathy. The low proportion of positive cases in the asymmetric microaneurysm detection problem causes preprocessing to treat microaneurysms as noise to be eliminated. To obtain a binary image containing microaneurysms, the object was segmented by a symmetry algorithm, which is a combination of the connected components and SSA methods. Next, a candidate microaneurysm set was extracted by multifeature clustering of binary images. Finally, the candidate microaneurysms were mapped to the Radon frequency domain to achieve microaneurysm detection. In order to verify the feasibility of the algorithm, a comparative experiment was conducted on the combination of the connected components and SSA methods. In addition, PSNR, FSIM, SSIM, fitness value, average CPU time and other indicators were used as evaluation standards. The results showed that the overall performance of the binary image obtained by the algorithm was the best. Last but not least, the accuracy of the detection method for microaneurysms in this paper reached up to 93.24%, which was better than that of several classic microaneurysm detection methods in the same period.

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Section: Msa-k Algorithmmentioning

confidence: 99%