Title :
Computational cancer detection of pathological images based on an optimization method for color-index local auto-correlation feature extraction
Author :
Jia Qu ; Nosato, Hirokazu ; Sakanashi, Hidenori ; Takahashi, Eiichi ; Terai, Kensuke ; Hiruta, Nobuyuki
Author_Institution :
Dept. of Intell. Interaction Technol., Univ. of Tsukuba, Tsukuba, Japan
fDate :
April 29 2014-May 2 2014
Abstract :
Aiming to lessen the burdens of the pathologist with efficient diagnosis assistance, this paper proposes a cancer detection method for pathological images utilizing color features based on color-index local auto-correlations (CILAC), applied to color-indexed images to utilize co-occurrence information about indexed pixels. Moreover, a method for the automatic optimization of feature extraction is also proposed. Based on a database including both benign and cancerous pathological images, experimental results show enhanced performance compared to prior research, which demonstrate the effectiveness of the proposed cancer detection method.
Keywords :
biomedical optical imaging; cancer; feature extraction; medical image processing; optimisation; CILAC; cancerous pathological images; color-index local autocorrelation feature extraction; color-indexed images; computational cancer detection; efficient diagnosis assistance; optimization method; Cancer; Cancer detection; Feature extraction; Image color analysis; Indexes; Pathology; Shape; CILAC; cancer detection; feature extraction; optimization; pathological images;
Conference_Titel :
Biomedical Imaging (ISBI), 2014 IEEE 11th International Symposium on
Conference_Location :
Beijing
DOI :
10.1109/ISBI.2014.6867997
