File(s) not publicly available

A fusion of neural network based auto-associator and classifier for the classification of microcalcification patterns

conference contribution
posted on 06.12.2017, 00:00 authored by Rinku PanchalRinku Panchal, Brijesh VermaBrijesh 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.

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

794

End Page

799

Number of Pages

6

Start Date

01/01/2004

ISBN-10

3540239316

Location

: Calcutta, India

Publisher

Springer

Place of Publication

Berlin, Germany

Peer Reviewed

Yes

Open Access

No

External Author Affiliations

Faculty of Informatics and Communication; TBA Research Institute;

Era Eligible

Yes

Name of Conference

ICONIP (Conference)