Boundary-precise segmentation of nucleus and plasma of leukocytes

Abstract

The exact segmentation of nucleus and plasma of a white blood cell (leukocyte) is the basis for the creation of an automatic, image based differential white blood cell count(WBC). In this contribution we present an approach for the according segmentation of leukocytes. For a valid classification of the different cell classes, a precise segmentation is essential. Especially concerning immature cells, which can be distinguished from their mature counterparts only by small differences in some features, a segmentation of nucleus and plasma has to be as precise as possible, to extract those differences. Also the problems with adjacent erythrocyte cells and the usage of a LED illumination are considered. The presented approach can be separated into several steps. After preprocessing by a Kuwahara-filter, the cell is localized by a simple thresholding operation, afterwards a fast-marching method for the localization of a rough cell boundary is defined. To retrieve the cell area a shortest-path-algorithm is applied next. The cell boundary found by the fast-marching approach is finally enhanced by a post-processing step. The concluding segmentation of the cell nucleus is done by a threshold operation. An evaluation of the presented method was done on a representative sample set of 80 images recorded with LED illumination and a 63-fold magnification dry objective. The automatically segmented cell images are compared to a manual segmentation of the same dataset using the Dice-coefficient as well as Hausdorff-distance. The results show that our approach is able to handle the different cell classes and that it improves the segmentation quality significantly

Leukemic cells segmentation algorithm based on molecular spectral imaging technology

“…This is due to the qualities of segmentation directly influencing on the subsequent feature extraction and recognition. There has been some work on white blood cells detection in the automatic recognition system based on microscopic blood images [15,17], yet there are still some difficulties because of the limited information of images captured by traditional microscopic CCD cameras.…”

A color and shape based algorithm for segmentation of white blood cells in peripheral blood and bone marrow images

“…These methods usually work on the RGB color space; however, there also exist some studies that work on other color spaces [such as the HSV and La*b* color spaces] for better quantifying visual differences between different image components. Additionally, it is possible to preprocess images with different techniques including filtering , histogram equalization , and contrast enhancement for noise elimination.…”