Image Segmentation Through an Iterative Algorithm of the Mean Shift

Morales, Roberto; Domínguez, Didier; Torres, Esley; Sossa, Juan H.

doi:10.5772/50474

Cited by 6 publications

(1 citation statement)

References 21 publications

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“…Moreover, in Figure 7, the following question is present: ¿Which image to choose or which to select as the best processed image? The answer to this question is not direct, because it depends on the aim of observer or from the application itself; that is, segmentation is heavily dependent on the application [18]. A theoretical analysis of the h parameter and its influence will appear in an upcoming publication.…”

Section: Experimental Results Discussionmentioning

confidence: 99%

SARS-CoV-2: Enhancement and Segmentation of High-ResolutionMicroscopy Images. Part I

Rodríguez

Mondeja²,

Valdés

et al. 2020

Preprint

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Possibly, and due to poor eating habits and unhealthy lifestyle, many virus are transmitted to human people. Such is the case, of the novel coronavirus SARS-Cov-2, which has expanded of exponential way, practically, to whole world population. For this reason, the study of real microscopic images of this coronavirus is of great importance. The SARS-Cov-2 images were captured from nasopharyngeal samples of Cuban symptomatic individuals (RT-PCR positives for SARS-CoV-2), and processed via scanning electron microscopy. However, many times these microscopic images present some blurring problems, which are always susceptible to be improved. The aim of this work is to propose new computational methods to carry out enhancement and segmentation of SARS-Cov-2 high-resolution microscopic images. Moreover, due to the importance of the obtained results, this first work will be addressed to the application of the proposed algorithm. The proposed strategy obtained very satisfactory results, and we validated its performance, together with specialist physicians, on a set of 1005 images. A second paper will deeply analyze the theory related to these algorithms

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Section: Experimental Results Discussionmentioning

confidence: 99%