PROCEEDINGS OF THE ITE WINTER ANNUAL CONVENTION
Online ISSN : 2424-2306
Print ISSN : 1343-4357
ISSN-L : 1343-4357
2009
Session ID : 5-2
Conference information

5-2 Anomaly Detection from Pathology Image using Higher-order Local Autocorrelation Features
Tsukasa KURIHARAHirokazu NOSATOHidenori SAKANASHIMasahiro MURAKAWATatsumi FURUYATetsuya HIGUCHINobuyuki OTSUKensuke TERAINobuyuki HIRUTANoriaki KAMEDA
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CONFERENCE PROCEEDINGS FREE ACCESS

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Abstract
This paper proposes computer aided diagnosis (CAD) system that uses the image recognition technique based on the higher-order local auto-correlation features (HLAC). The computational simulation implied that the proposed system could detect the gastric biopsy image containing cancer.
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© 2009 The Institute of Image Information and Television Engineers
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