(al 2019-1-3-1-KK-2019-00007 Innovációs szolgáltató bázis létrehozása diagnosztikai,
terápiás és kutatási célú kiberorvosi rendszerek fejlesztésére pályáz)
Subjects:
Health sciences
Digitization in pathology and cytology labs is now widespread, a significant shift
from a decade ago when few doctors used image processing tools. Despite unchanged
scanning times due to excitation in fluorescent imaging, advancements in computing
power and software have enabled more complex algorithms, yielding better-quality results.
This study evaluates three nucleus segmentation algorithms for ploidy analysis using
propidium iodide-stained digital WSI slides. Our goal was to improve segmentation
accuracy to more closely match DNA histograms obtained via flow cytometry, with the
ultimate aim of enhancing the calibration method we proposed in a previous study,
which seeks to align image cytometry results with those from flow cytometry. We assessed
these algorithms based on raw segmentation performance and DNA histogram similarity,
using confusion-matrix-based metrics. Results indicate that modern algorithms perform
better, with F1 scores exceeding 0.845, compared to our earlier solution’s 0.807,
and produce DNA histograms that more closely resemble those from the reference FCM
method.
