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A fusion of neural network based auto-associator and classifier for the classification of microcalcification patterns
conference contributionposted on 2017-12-06, 00:00 authored by Rinku PanchalRinku Panchal, Brijesh Verma
This paper presents a novel approach to combine a neural network based auto-associator and a classifier for the classification of microcalcification patterns. It explores the auto-associative and classification abilities of a neural network approach for the classification of rnicrocalcification patterns into benign and malignant using 14 image structure features. The proposed technique used combination of two neural networks; auto-associator and classifier for classification of microcalcification. It obtained 88.1% classification rate for testing dataset and 100% classification rate for training dataset.
Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)
Parent TitleProceedings of the 11th International Conference on Neural Information Processing.
Number of Pages6
Location: Calcutta, India
Place of PublicationBerlin, Germany
External Author AffiliationsFaculty of Informatics and Communication; TBA Research Institute;