Katarina Mele and Aleš Leonardis (2003) Detection of Ductus in Mammary Gland Tissue by Computer Vision. In: 5th International Conference on Simulations in Biomedicine.
In cell nucleus images of mammary gland tissue, both features of the nucleus and nuclei group shapes serve as cancer diagnosis criteria. Also, further treatment is dependent on the information about the cell nucleus spatial arrangement formed by malignant, potentially malignant, and normal ductus. In this paper we present an automatic image analysis method that we developed for detecting the structures of nucleus clumps that represent boundaries of ductus. The method consist of the following stages applied in succession: segmentation with a threshold, greedy algorithm, relaxation, and graph search. We tested our algorithm on images of mammary glands tissue. The results indicate that the method can distinguish between healthy ducts that have regular shapes and the malignant ducts (ductal carcinoma in situ) that have irregular shapes with boundaries appearing also inside the ducts. This automatics procedure is a new approach in the area of cytometry and DCIS, which we believe will lead to a more reliable and objective evaluation of architectural characterization of nuclei group.
|Item Type: ||Conference or Workshop Item (Paper)|
|Keywords: ||computer vision, segmentation, relaxation, graph search, greedy algorithm, breast cancer, cytology|
|Language of Content: ||English|
|Related URLs: |
|Institution: ||University of Ljubljana|
|Department: ||Faculty of Computer and Information Science|
|Divisions: ||Faculty of Computer and Information Science > Computer Vision Laboratory|
|Item ID: ||132|
|Date Deposited: ||16 Aug 2004|
|Last Modified: ||11 Dec 2013 11:19|
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