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Histopathological image analysis : a review

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Gurcan, Metin N., Boucheron, Laura E., Can, Ali, Madabhushi, Anant, Rajpoot, Nasir M. and Yener, Bülent (2009) Histopathological image analysis : a review. IEEE Reviews in Biomedical Engineering, Vol.2 . pp. 147-171. doi:10.1109/RBME.2009.2034865

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Official URL: http://dx.doi.org/10.1109/RBME.2009.2034865

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Abstract

Over the past decade, dramatic increases in computational power and improvement in image analysis algorithms have allowed the development of powerful computer-assisted analytical approaches to radiological data. With the recent advent of whole slide digital scanners, tissue histopathology slides can now be digitized and stored in digital image form. Consequently, digitized tissue histopathology has now become amenable to the application of computerized image analysis and machine learning techniques. Analogous to the role of computer-assisted diagnosis (CAD) algorithms in medical imaging to complement the opinion of a radiologist, CAD algorithms have begun to be developed for disease detection, diagnosis, and prognosis prediction to complement the opinion of the pathologist. In this paper, we review the recent state of the art CAD technology for digitized histopathology. This paper also briefly describes the development and application of novel image analysis technology for a few specific histopathology related problems being pursued in the United States and Europe.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
R Medicine > RB Pathology
Divisions: Faculty of Science > Computer Science
Library of Congress Subject Headings (LCSH): Histology, Pathological, Image processing -- Digital techniques, Medical innovations, Diagnosis -- Data processing
Journal or Publication Title: IEEE Reviews in Biomedical Engineering
Publisher: IEEE
ISSN: 1937-3333
Official Date: 30 October 2009
Dates:
DateEvent
30 October 2009Published
Volume: Vol.2
Page Range: pp. 147-171
DOI: 10.1109/RBME.2009.2034865
Status: Peer Reviewed
Access rights to Published version: Open Access
Funder: National Cancer Institute (U.S.) (NCI), National Library of Medicine (U.S.) (NLM), American Cancer Society, Children's Neuroblastoma Cancer Foundation, Wallace H. Coulter Foundation, New Jersey Commission on Cancer Research, Cancer Institute of New Jersey, Rutgers University, Ohio State University. Center for Clinical and Translational Science, United States. Dept. of Defense (DoD)
Grant number: R01 CA134451 (NCI), R01CA136535-01 (NCI), ARRA-NCl-3 21CA127186–02S1 (NCI), R21CA127186–01 (NCI), R03CA128081-01 (NCI), and R03CA143991-01 (NCI), R01 LM010119 (NLM), W81XWH-07-1-0402 (DoD)

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