Accurate detection of individual cell nuclei in microscopy images is an essential and fundamental task for many biological studies. In particular, multivariate fluorescence microscopy is used to observe different aspects of cells in cultures. Manual detection of individual cell nuclei by visual inspection is time consuming, and prone to induce subjective bias. This makes automatic detection of cell nuclei essential for large-scale, objective studies of cell cultures. Blur, clutter, bleed-through, imaging noise and touching and partially overlapping nuclei with varying sizes and shapes make automated detection of individual cell nuclei a challenging task using image analysis. In this paper we propose a new automated method for fast and robust detection of individual cell nuclei based on their radial symmetric nature in fluorescence in-situ hybridization (FISH) images obtained via confocal microscopy. The main contributions are two-fold. 1) This work presents a more accurate cell nucleus detection system using the fast radial symmetry transform (FRST). 2) The proposed cell nucleus detection system is robust against most occlusions and variations in size and moderate shape deformations. We evaluate the performance of the proposed algorithm using precision/recall rates, Fβ-score and root-mean-squared distance (RMSD) and show that our algorithm provides improved detection accuracy compared to existing algorithms.
- Cell nucleus detection
- FISH images
- histogram thresholding
ASJC Scopus subject areas
- Radiological and Ultrasound Technology
- Computer Science Applications
- Electrical and Electronic Engineering