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Abstract
Currently, colon cancer diagnosis is based on manual assessment of tissue samples stained with hematoxylin and eosin (H&E). This is a high volume, time consuming, and subjective task which could be aided by automatic cancer detection. We propose an algorithm for automatic cancer detection within WSI H&E stains using a multi class colon tissue classifier based on features extracted from 5 different color representations. Approx. 32000 tissue patches were extracted for the classifier from manual annotations of 9 representative colon tissue types from 74 WSI H&E stains. Colon tissue classifiers based on gray level or color features were trained using leave-one-out forward selection. The best colon tissue classifier was based on color texture features obtaining an average tissue precision-recall (PR) area under the curve (AUC) of 0.886 and a cancer PR-AUC of 0.950 on 20 validation WSI H&E stains.
Originalsprog | Engelsk |
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Titel | Computational Pathology and Ophthalmic Medical Image Analysis : First International Workshop, COMPAY 2018, and 5th International Workshop, OMIA 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, 16-20 September 2018, Proceedings |
Redaktører | Zeike Taylor, Hrvoje Bogunovic, David Snead, Mona K. Garvin, Xin Jan Chen, Francesco Ciompi, Yanwu Xu, Lena Maier-Hein, Mitko Veta, Emanuele Trucco, Danail Stoyanov, Nasir Rajpoot, Jeroen van der Laak, Anne Martel, Stephen McKenna |
Antal sider | 8 |
Forlag | Springer |
Publikationsdato | 2018 |
Sider | 61-68 |
ISBN (Trykt) | 978-3-030-00948-9 |
ISBN (Elektronisk) | 978-3-030-00949-6 |
DOI | |
Status | Udgivet - 2018 |
Begivenhed | 1st International Workshop on Computational Pathology, COMPAY 2018, and 5th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2018 - Granada, Spanien Varighed: 16 okt. 2018 → 20 okt. 2018 |
Konference
Konference | 1st International Workshop on Computational Pathology, COMPAY 2018, and 5th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2018 |
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Land/Område | Spanien |
By | Granada |
Periode | 16/10/2018 → 20/10/2018 |
Navn | Lecture Notes in Computer Science |
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Vol/bind | 11039 |
ISSN | 0302-9743 |
Fingeraftryk
Dyk ned i forskningsemnerne om 'Exploiting multiple color representations to improve colon cancer detection in whole slide H&E stains'. Sammen danner de et unikt fingeraftryk.Projekter
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Automated cancer diagnostics in histopathological images
Jørgensen, A. S.
01/12/2015 → …
Projekter: Projekt › Forskning