Publications

@article{gonzalez-castro_combined_2009,

title = {A combined and intelligent new segmentation method for boar semen based on thresholding and watershed transform},

author = {V González-Castro and Enrique Alegre and P Morala-Argüello and SA Suarez},

url = {https://www.research.ed.ac.uk/en/publications/a-combined-and-intelligent-new-segmentation-method-for-boar-semen},

year  = {2009},

date = {2009-01-01},

journal = {International Journal of Imaging},

volume = {2},

number = {9 S},

pages = {70–80},

abstract = {This work presents a new method to segment images of alive and dead spermatozoa in ositive phase contrast. This method improves previous segmentation methods applying an intelligent threshold combined with watershed segmentation. First, it applies an intelligent thresholding segmentation that changes the value of threshold when the binary image obtained is not fulfill the surface and eccentricity factors. Then, using the same automatic criteria, the bad segmented images are processed by means of the watershed transform. Using this new method a 90.96% of the spermatozoa have been correctly segmented. This approach could be useful to commercial Computer Assisted Semen Analysis systems that need new and more accurate segmentation processes.},

note = {Publisher: Indian Society for Development and Environment Research},

keywords = {images, segmentation, segmentation method, semen, threshold, watershed},

pubstate = {published},

tppubtype = {article}

}

@article{gonzalez_castro_combined_2009,

title = {A combined and intelligent new segmentation method for boar semen based on thresholding and watershed transform},

author = {Víctor González Castro and Enrique Alegre and P Morala Argüello and SA Suarez},

url = {https://www.research.ed.ac.uk/en/publications/a-combined-and-intelligent-new-segmentation-method-for-boar-semen},

year  = {2009},

date = {2009-01-01},

journal = {International Journal of Imaging},

volume = {2},

number = {9 S},

pages = {70–80},

abstract = {This work presents a new method to segment images of alive and dead spermatozoa in ositive phase contrast. This method improves previous segmentation methods applying an intelligent threshold combined with watershed segmentation. First, it applies an intelligent thresholding segmentation that changes the value of threshold when the binary image obtained is not fulfill the surface and eccentricity factors. Then, using the same automatic criteria, the bad segmented images are processed by means of the watershed transform. Using this new method a 90.96% of the spermatozoa have been correctly segmented. This approach could be useful to commercial Computer Assisted Semen Analysis systems that need new and more accurate segmentation processes.},

note = {Publisher: Indian Society for Development and Environment Research},

keywords = {images, segmentation, segmentation method, semen, threshold, watershed},

pubstate = {published},

tppubtype = {article}

}