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|Type:||Artigo de evento|
|Title:||Cell Nuclei Segmentation In Noisy Images Using Morphological Watersheds|
De Andrade Netto M.L.
|Abstract:||A major problem in image processing and analysis is the segmentation of its components. Many computer vision tasks process image regions after segmentation, and the minimization of errors is then crucial for a good automatic inspection system. This paper presents an applied work on automatic segmentation of cell nuclei in digital noisy images. One of the major problems when using morphological watersheds is oversegmentation. By using an efficient homotopy image modification module, we prevent oversegmentation. This module utilizes diverse operations, such as sequential filters, distance transforms, opening by reconstruction, top hat, etc., some in parallel, some in cascade form, leading to a new set of internal and external cell nuclei markers. Very good results have been obtained and the proposed technique should facilitate better analysis of visual perception of cell nuclei for human and computer vision. All steps are presented, as well as the associated images. Implementations were done in the Khoros system using the MMach toolbox.|
|Appears in Collections:||Unicamp - Artigos e Outros Documentos|
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