Segmentation of fluorescence microscopy images using three dimensional active contours with inhomogeneity correction
Soonam Lee, Paul Salama, Kenneth William Dunn, Edward J. Delp · 2017
Image segmentation is an important step in the quantitative analysis of fluorescence microscopy data. Since fluorescence microscopy volumes suffer from intensity inhomogeneity, low image contrast and limited depth resolution, poor edge details, and irregular structure shape, segmentation still remains a challenging problem. This paper describes a nuclei segmentation method for fluorescence microscopy based on the use of three dimensional (3D) active contours with inhomogeneity correction. The correction information utilizes 3D volume information while addressing intensity inhomogeneity across vertical and horizontal directions. Experimental results demonstrate that the proposed method achieves better performance than other reported methods.