@inproceedings{52ba3d9d950243cd90879c9514407ca3,
title = "Multifractal feature descriptor for diagnosing liver and prostate cancers in H&E stained histologic images",
abstract = "Histologic imaging plays an important role in discriminating cancerous tissues of several body organs. However, the human histopathological examinations may be subjective and error prone, because of the complexity of the appearances of the histologic texture. These limitations can be overcome by adopting quantitative computational methods with human histopathological examination routines. This study proposes a new feature descriptor to characterize texture of histologic images. The proposed method derives a discriminative feature space by observing the self-similarity characteristics of the texture based on fractal geometry. The merit of utilizing fractal geometry to describe the histologic texture is assessed by a classification experiment. The experimental results indicate that the proposed feature descriptor can classify cancer and non-cancer tissues of histologic images of liver and prostate images around 95% of correct classification rate.",
keywords = "Classification, Feature descriptors, Fractal, Histology, Multifractal",
author = "C. Atupelage and H. Nagahashi and M. Yamaguchi and T. Abe and A. Hashiguchi and M. Sakamoto",
year = "2012",
month = aug,
day = "15",
doi = "10.1109/ISBI.2012.6235543",
language = "English",
isbn = "9781457718588",
series = "Proceedings - International Symposium on Biomedical Imaging",
pages = "298--301",
booktitle = "2012 9th IEEE International Symposium on Biomedical Imaging",
note = "2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2012 ; Conference date: 02-05-2012 Through 05-05-2012",
}
