TY - GEN
T1 - Multifractal feature descriptor for grading Hepatocellular carcinoma
AU - Atupelage, C.
AU - Nagahashi, H.
AU - Yamaguchi, M.
AU - Abe, T.
AU - Hashiguchi, A.
AU - Sakamoto, M.
PY - 2012/12/1
Y1 - 2012/12/1
N2 - This paper presents a textural feature descriptor that can be effectively utilized for grading Hepatocellular carcinoma (HCC) histopathological images. The proposed feature descriptor observes the local and spatial characteristics of the texture by utilizing multifractal computation, and it is incorporated with a bag-of-feature (BOF)-based classification model to classify a set of images. We compare the proposed feature descriptor with four well-founded feature descriptors in the experiments, and benchmark the classification performances. The benchmarked results indicated the significance of the multifractal feature descriptor.
AB - This paper presents a textural feature descriptor that can be effectively utilized for grading Hepatocellular carcinoma (HCC) histopathological images. The proposed feature descriptor observes the local and spatial characteristics of the texture by utilizing multifractal computation, and it is incorporated with a bag-of-feature (BOF)-based classification model to classify a set of images. We compare the proposed feature descriptor with four well-founded feature descriptors in the experiments, and benchmark the classification performances. The benchmarked results indicated the significance of the multifractal feature descriptor.
UR - http://www.scopus.com/inward/record.url?scp=84874571683&partnerID=8YFLogxK
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M3 - Conference contribution
AN - SCOPUS:84874571683
SN - 9784990644109
T3 - Proceedings - International Conference on Pattern Recognition
SP - 129
EP - 132
BT - ICPR 2012 - 21st International Conference on Pattern Recognition
T2 - 21st International Conference on Pattern Recognition, ICPR 2012
Y2 - 11 November 2012 through 15 November 2012
ER -