Classifier-based Cell Segmentation from Confocal Microscopy Images
نویسندگان
چکیده
In vivo observation and tracking of cell division in the Arabidopsis thaliana root meristem, by time-lapse confocal microscopy, is central to biology research. This paper discusses an automatic cell segmentation method, which selects the best cell candidates from a starting watershed segmentation. The selection of individual cells is obtained using a Support Vector Machine (SVM) classifier, based on the shape and edge strength of the cells’ contour. The result is an improved segmentation, which is largely pruned of badly segmented cells.
منابع مشابه
Evaluation of atlas selection strategies for atlas-based image segmentation with application to confocal microscopy images of bee brains.
This paper evaluates strategies for atlas selection in atlas-based segmentation of three-dimensional biomedical images. Segmentation by intensity-based nonrigid registration to atlas images is applied to confocal microscopy images acquired from the brains of 20 bees. This paper evaluates and compares four different approaches for atlas image selection: registration to an individual atlas image ...
متن کاملStatistical region based active contour using a fractional entropy descriptor: Application to nuclei cell segmentation in confocal microscopy images
We propose an unsupervised statistical region based active contour approach integrating an original fractional entropy measure for image segmentation with a particular application to single channel actin tagged fluorescence confocal microscopy image segmentation. Following description of statistical based active contour segmentation and the mathematical definition of the proposed fractional ent...
متن کاملFractional Entropy Based Active Contour Segmentation of Cell Nuclei in Actin-Tagged Confocal Microscopy Images
In the framework of cell structure characterization for predictive oncology, we propose in this paper an unsupervised statistical region based active contour approach integrating an original fractional entropy measure for single channel actin tagged fluorescence confocal microscopy image segmentation. Following description of statistical based active contour segmentation and the mathematical de...
متن کاملA Pulse Coupled Neural Network Segmentation Algorithm for Reflectance Confocal Images of Epithelial Tissue
Automatic segmentation of nuclei in reflectance confocal microscopy images is critical for visualization and rapid quantification of nuclear-to-cytoplasmic ratio, a useful indicator of epithelial precancer. Reflectance confocal microscopy can provide three-dimensional imaging of epithelial tissue in vivo with sub-cellular resolution. Changes in nuclear density or nuclear-to-cytoplasmic ratio as...
متن کاملAutomatic Analysis of Leishmania Infected Microscopy Images via Gaussian Mixture Models
This work addresses the issue of automatic organic component detection and segmentation in confocal microscopy images. The proposed method performs cellular/parasitic identification through adaptive segmentation using a two-level Otsu’s Method. Segmented regions are divided using a rule-based classifier modeled on a decreasing harmonic function and a Support Vector Machine trained with features...
متن کامل