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A fusion of neural network based auto-associator and classifier for the classification of microcalcification patterns
conference contribution
posted on 2017-12-06, 00:00 authored by Rinku PanchalRinku Panchal, Brijesh VermaThis 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.
Funding
Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)
History
Parent Title
Proceedings of the 11th International Conference on Neural Information Processing.Start Page
794End Page
799Number of Pages
6Start Date
2004-01-01ISBN-10
3540239316Location
: Calcutta, IndiaPublisher
SpringerPlace of Publication
Berlin, GermanyPeer Reviewed
- Yes
Open Access
- No
External Author Affiliations
Faculty of Informatics and Communication; TBA Research Institute;Era Eligible
- Yes