Effects of Interpolation on Segmentation in Cell Imaging

Abstract

In digital image processing and computer vision applications for microscopy imaging, calculating image features is a frequent task. Features related to intensity, color and morphology are used to classify cells and other objects. The precision of segmentation influences the calculated feature values and can affect the results of classification. Therefore, achieving a high precision in segmentation is very important. In this work, the effects of interpolation on the precision of image segmentation were studied using instances of cell microscopy images and different interpolation and segmentation methods. The goal was to determine quantitatively to what extent improvements in segmentation precision can be obtained through previous interpolation of the images. This effect can be particularly important for small objects, whose images might be deteriorated due to limitations in the camera’s resolution. The results show that an improvement in the precision of segmentation can be obtained by previously interpolating the images.