NDLI: Robust automatic breast cancer staging using a combination of functional genomics and image-omics

Content Provider	IEEE Xplore Digital Library
Author	Hai Su Yong Shen Fuyong Xing Xin Qi Hirshfield, K.M. Lin Yang Foran, D.J.
Copyright Year	2015
Description	Author affiliation: J. Crayton Pruitt Family Dept. of Biomed. Eng., Univ. of Florida, Gainesville, FL, USA (Hai Su; Fuyong Xing; Lin Yang) \|\| Rutgers Cancer Inst. of New Jersey, New Brunswick, NJ, USA (Xin Qi; Hirshfield, K.M.; Foran, D.J.) \|\| Genetics Inst., Univ. of Florida, Gainesville, FL, USA (Yong Shen)
Abstract	Breast cancer is one of the leading cancers worldwide. Precision medicine is a new trend that systematically examines molecular and functional genomic information within each patient's cancer to identify the patterns that may affect treatment decisions and potential outcomes. As a part of precision medicine, computer-aided diagnosis enables joint analysis of functional genomic information and image from pathological images. In this paper we propose an integrated framework for breast cancer staging using image-omics and functional genomic information. The entire biomedical imaging informatics framework consists of image-omics extraction, feature combination, and classification. First, a robust automatic nuclei detection and segmentation is presented to identify tumor regions, delineate nuclei boundaries and calculate a set of image-based morphological features; next, the low dimensional image-omics is obtained through principal component analysis and is concatenated with the functional genomic features identified by a linear model. A support vector machine for differentiating stage I breast cancer from other stages are learned. We experimentally demonstrate that compared with a single type of representation (image-omics), the combination of image-omics and functional genomic feature can improve the classification accuracy by 3%.
Starting Page	7226
Ending Page	7229
File Size	1651717
Page Count	4
File Format	PDF
ISSN	1557170X
e-ISBN	9781424492718
DOI	10.1109/EMBC.2015.7320059
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-08-25
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Genomics Bioinformatics Breast cancer Feature extraction Tumors Image segmentation
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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