{{ t.heroP1 }}
{{ t.heroP2 }}
{{ t.workflowP }}
{{ t.diffP }}
{{ t.diff1P }}
{{ t.diff2P1 }}{{ t.diff2PBold }}{{ t.diff2P2 }}
{{ t.demoP }}
import numpy as np from skimage import filters, measure, morphology # Segmentation des noyaux — canal 2 nuclei = image[..., 2] mask = nuclei > filters.threshold_otsu(nuclei) mask = morphology.remove_small_objects(mask, 64) # Mesures morphométriques labels = measure.label(mask) table = measure.regionprops_table( labels, nuclei, properties=("area", "circularity", "mean_intensity"), )
{{ t.pq1P }}
{{ t.pq2P }}
{{ t.secP }}
{{ t.fmtP }}
{{ t.faq1A }}
{{ t.faq2A }}
{{ t.faq3A }}
{{ t.faq4A }}
{{ t.faq5A }}
{{ t.faq6A }}
{{ t.contactP }}