@inproceedings{2603ef337368475f85c87721316357ff,
title = "Unsupervised tissue image segmentation through object-oriented texture",
abstract = "This paper presents a new algorithm for the unsupervised segmentation of tissue images. It relies on using the spatial information of cytological tissue components. As opposed to the previous study, it does not only use this information in defining its homogeneity measures, but it also uses it in its region growing process. This algorithm has been implemented and tested. Its visual and quantitative results are compared with the previous study. The results show that the proposed segmentation algorithm is more robust in giving better accuracies with less number of segmented regions.",
keywords = "Image segmentation, Quantitative medical image analysis, Texture analysis",
author = "Tosun, \{Akif Burak\} and Cenk Sokmensuer and Cigdem Gunduz-Demir",
year = "2010",
doi = "10.1109/ICPR.2010.616",
language = "English",
isbn = "9780769541099",
series = "Proceedings - International Conference on Pattern Recognition",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2516--2519",
booktitle = "Proceedings - 2010 20th International Conference on Pattern Recognition, ICPR 2010",
address = "United States",
}