An Anisotrophic Diffusion Algorithm with Optimized Rotation Invariance
Mustererkennung 2000, 22. DAGM-Symposium
Adaptive Thresholding Based Cell Segmentation for Cell-Destruction Activity Verification
AIPR '06 Proceedings of the 35th Applied Imagery and Pattern Recognition Workshop
Cell Nuclei Segmentation Combining Multiresolution Analysis, Clustering Methods and Colour Spaces
IMVIP '07 Proceedings of the International Machine Vision and Image Processing Conference
Graph-based tools for microscopic cellular image segmentation
Pattern Recognition
A novel cell segmentation method and cell phase identification using Markov model
IEEE Transactions on Information Technology in Biomedicine
Segmentation of complex nucleus configurations in biological images
Pattern Recognition Letters
Unsupervised segmentation based on robust estimation and color active contour models
IEEE Transactions on Information Technology in Biomedicine
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In this paper we focus on the segmentation problem of specific chained configurations in images taken from colon tissues. The proposed technique uses a priori information about the general structure and the relationship between epithelial cells nuclei and encapsulates the human behaviour on the critical regions between nuclei. After the background detection is performed, the points with high concavity from the boundaries of the nuclei structures are detected. A set of templates and rules are established by analysing the inter-nuclei regions. These rules are used to validate and to pair the concave points so that their connecting lines to indicate the separation regions between nuclei. The evaluation of the proposed method is made with precision, recall and accuracy measures.