Innovációs szolgáltató bázis létrehozása diagnosztikai, terápiás és kutatási célú
kiberorvosi ren...(2019-1-3-1-KK-2019-00007) Támogató: NKFIH
Szakterületek:
Érzékelők
Érzékelő rendszerek (látórendszer, hallórendszer)
Image quality, resolution and scanning time are critical in digital pathology. In
order to create a high-resolution digital image, the scanner systems execute stitching
algorithms to the digitized images. Due to the heterogeneity of the tissue sample,
complex optical path, non-acceptable sample quality or rapid stage movement, the intensities
on pictures can be uneven. The evincible and visible intensity distortions can have
negative effect on diagnosis and quantitative analysis. Utilizing the common areas
of the neighboring field-of-views, we can estimate compensations to eliminate the
inhomogeneities. We implemented and validated five different approaches for compensating
output images created with an area scanner system. The proposed methods are based
on traditional methods such as adaptive histogram matching, regression-based corrections
and state-of-the art methods like the background and shading correction (BaSiC) method.
The proposed compensation methods are suitable for both brightfield and fluorescent
images, and robust enough against dust, bubbles, and optical aberrations. The proposed
methods are able to correct not only the fixed-pattern artefacts but the stochastic
uneven illumination along the neighboring or above field-of-views utilizing iterative
approaches and multi-focal compensations.
