dc.creatorRojas, Oswaldo
dc.creatorForero Vargas, Manuel Guillermo
dc.creatorMen?ndez, Jos? Manuel
dc.creatorJones, Angharad
dc.creatorDewitte, Walter
dc.creatorMurray, James
dc.date2021-04-27T21:09:06Z
dc.date2021-04-27T21:09:06Z
dc.date2020-11-28
dc.date.accessioned2023-08-31T19:06:42Z
dc.date.available2023-08-31T19:06:42Z
dc.identifierRojas, O., Forero, M. G., Men?ndez, J. M., Jones, A., Dewitte, W., & Murray, J. A. H. (2020). Segmentation of meristem cells by an automated optimization algorithm. Applied Sciences (Switzerland), 10(23), 1-16. doi:10.3390/app10238523
dc.identifier2076-3417
dc.identifierhttps://www.mdpi.com/2076-3417/10/23/8523
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8555593
dc.descriptionMeristem cells are irregularly shaped and appear in confocal images as dark areas surrounded by bright ones. Images are characterized by regions of very low contrast and absolute loss of edges deeper into the meristem. Edges are blurred, discontinuous, sometimes indistinguishable, and the intensity level inside the cells is similar to the background of the image. Recently, a technique called Parametric Segmentation Tuning was introduced for the optimization of segmentation parameters in diatom images. This paper presents a PST-tuned automatic segmentation method of meristem cells in microscopy images based on mathematical morphology. The optimal parameters of the algorithm are found by means of an iterative process that compares the segmented images obtained by successive variations of the parameters. Then, an optimization function is used to determine which pair of successive images allows for the best segmentation. The technique was validated by comparing its results with those obtained by a level set algorithm and a balloon segmentation technique. The outcomes show that our methodology offers better results than two free available state-of-the-art alternatives, being superior in all cases studied, losing 9.09% of the cells in the worst situation, against 75.81 and 25.45 obtained in the level set and the balloon segmentation techniques, respectively. The optimization method can be employed to tune the parameters of other meristem segmentation methods.
dc.descriptionUniversidad de Ibagu?
dc.languageen
dc.publisherApplied Sciences
dc.subjectMeristem cells
dc.subjectMorphology
dc.subjectSegmentation
dc.subjectReceiver-operating characteristic
dc.titleSegmentation of Meristem Cells by an Automated Optimization Algorithm
dc.typeArticle


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