Histopathological image understanding is a demanding task for pathologists, involving the risky decision of confirming or denying the presence of cancer. What is more, the increased incidence of the disease, on the one hand, and the current prevention screening, on the other, result in an immense quantity of such pictures. For the colorectal cancer type in particular, a computational approach attempts to learn from small manually annotated portions of images and extend the findings to the complete ones. As the output of such techniques highly depends on the input variables, the current study conducts an investigation of the effect on the automatic contour detection that the choices for parameter values have from a cropped section to the complete image.
['Catalin Stoean', 'Ruxandra Stoean', 'Adrian Sandita', 'Cristian Mesina', 'Daniela Ciobanu', 'Gruia Cl']
Investigation on Parameter Effect for Semi-automatic Contour Detection in Histopathological Image Processing