NDLI: Iteratively training classifiers for circulating tumor cell detection

Content Provider	IEEE Xplore Digital Library
Author	Yunxiang Mao Zhaozheng Yin Schober, J.M.
Copyright Year	2015
Description	Author affiliation: Southern Illinois Univ. Edwardsville, IL, USA (Schober, J.M.) \|\| Missouri Univ. of Sci. & Technol., Rolla, MO, USA (Yunxiang Mao; Zhaozheng Yin)
Abstract	The number of Circulating Tumor Cells (CTCs) in blood provides an indication of disease progression and tumor response to chemotherapeutic agents. Hence, routine detection and enumeration of CTCs in clinical blood samples have significant applications in early cancer diagnosis and treatment monitoring. In this paper, we investigate two classifiers for image-based CTC detection: (1) Support Vector Machine (SVM) with hard-coded Histograms of Oriented Gradients (HoG) features; and (2) Convolutional Neural Network (CNN) with automatically learned features. For both classifiers, we present an effective and efficient training algorithm, by which the most representative negative samples are iteratively collected to accurately define the classification boundary between positive and negative samples. The two iteratively trained classifiers are validated on a challenging dataset with high performance.
Starting Page	190
Ending Page	194
File Size	732920
Page Count	5
File Format	PDF
ISBN	9781479923748
DOI	10.1109/ISBI.2015.7163847
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-04-16
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Tumors Blood Cancer Support vector machines Cells (biology) Feature extraction support vector machine circulating tumor cells iterative training convolutional neural network
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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