Abstract (EN):
The study of cancer cell invasion under the effect of different
conditions is fundamental for the understanding of
the cancer invasion mechanism and to test possible therapies
for its regulation. To simulate invasion across tissue
basement membrane, biologists established in vitro assays
with cancer cells invading extracellular matrix components.
However, analysis of such assays is manual, being timeconsuming
and error-prone, which motivates an objective
and automated analysis tool.
Towards automating such analysis we present a methodology
to detect cells in 3D matrix cell assays and correctly
estimate their invasion, measured by the depth of the penetration
in the gel. Detection is based on the sliding band
filter, by evaluating the gradient convergence and not intensity.
As such it can detect low contrast cells which otherwise
would be lost. For cell depth estimation we present a focus
estimator based on the convergence gradient¿s magnitude.
The final cell detection¿s precision and recall are of 0.896
and 0.910 respectively, and the average error in the cell¿s
position estimate is of 0.41µm, 0.37µm and 3.7µm in the
x, y and z directions, respectively.
Language:
English
Type (Professor's evaluation):
Scientific
No. of pages:
3
License type: