Title :
Selection of Tumor Areas and Segmentation of Nuclear Membranes in Tissue Confocal Images: A Fully Automated Approach
Author :
Cataldo, Santa Di ; Ficarra, Elisa ; Macii, Enrico
Author_Institution :
Politecnico di Torino, Turin
Abstract :
An accurate and standardized technique for tumor tissue segmentation is a critical step for monitoring and quantifying the activity of specific families of proteins involved in multi-factorial genetic pathologies. However, fully automated tissue and cell segmentation in clinical images presents many challenges related to the characteristics of the images that make traditional approaches substantially ineffective or incomplete. In this paper we present a fully-automated algorithm that is able to perform accurate and fast segmentation of tissue images. Experimental results on several real-life datasets demonstrate the high level of accuracy achievable thanks to our approach.
Keywords :
biomedical optical imaging; biomembranes; cancer; cellular biophysics; genetics; image segmentation; medical image processing; proteins; tumours; cell segmentation; fully-automated algorithm; multifactorial genetic pathologies; nuclear membranes; proteins; tissue confocal images; tumor segmentation; Active contours; Biomembranes; Cells (biology); Genetics; Image analysis; Image segmentation; Neoplasms; Pathology; Protein engineering; Robustness;
Conference_Titel :
Bioinformatics and Biomedicine, 2007. BIBM 2007. IEEE International Conference on
Conference_Location :
Fremont, CA
Print_ISBN :
978-0-7695-3031-4
DOI :
10.1109/BIBM.2007.10