A novel soft cluster neural network for the classification of suspicious areas in digital mammograms

Article


Verma, Brijesh, McLeod, Peter and Klevansky, Alan. 2009. "A novel soft cluster neural network for the classification of suspicious areas in digital mammograms." Pattern Recognition. 42 (9), pp. 1845-1852. https://doi.org/10.1016/j.patcog.2009.02.009
Article Title

A novel soft cluster neural network for the classification of suspicious areas in digital mammograms

ERA Journal ID4503
Article CategoryArticle
AuthorsVerma, Brijesh (Author), McLeod, Peter (Author) and Klevansky, Alan (Author)
Journal TitlePattern Recognition
Journal Citation42 (9), pp. 1845-1852
Number of Pages8
Year2009
Place of PublicationNetherlands
ISSN0031-3203
1873-5142
Digital Object Identifier (DOI)https://doi.org/10.1016/j.patcog.2009.02.009
Web Address (URL)http://www.sciencedirect.com/science/article/pii/S0031320309000764#
Abstract

This paper presents a novel soft cluster neural network technique for the classification of suspicious areas in digital mammograms. The technique introduces the concept of soft clusters within a neural network layer and combines them with least squares for optimising neural network weights. The idea of soft clusters is proposed in order to increase the generalisation ability of the neural network by providing a mechanism to more aptly depict the relationship between the input features and the subsequent classification as either a benign or malignant class. Soft clusters with least squares make the training process faster and avoid iterative processes which have many problems. The proposed neural network technique has been tested on the DDSM benchmark database. The results are analysed and discussed in this paper.

Keywordspattern classification; neural networks; clustering algorithms
ANZSRC Field of Research 2020469999. Other information and computing sciences not elsewhere classified
320602. Medical biotechnology diagnostics (incl. biosensors)
320222. Radiology and organ imaging
Public Notes

Files associated with this item cannot be displayed due to copyright restrictions.

Byline AffiliationsCentral Queensland University
Department of Health, Queensland
Institution of OriginUniversity of Southern Queensland
Permalink -

https://research.usq.edu.au/item/q2w46/a-novel-soft-cluster-neural-network-for-the-classification-of-suspicious-areas-in-digital-mammograms

  • 1677
    total views
  • 5
    total downloads
  • 0
    views this month
  • 0
    downloads this month

Export as

Related outputs

Road Severity Distance Calculation Technique using Deep Learning Predictions in 3-D Space
Perera, Asanka G. and Verma, Brijesh. 2022. "Road Severity Distance Calculation Technique using Deep Learning Predictions in 3-D Space." IEEE Access. 10, pp. 68000-68008. https://doi.org/10.1109/ACCESS.2022.3185997
Classification of benign and malignant patterns in digital mammograms for the diagnosis of breast cancer
Verma, Brijesh, McLeod, Peter and Klevansky, Alan. 2010. "Classification of benign and malignant patterns in digital mammograms for the diagnosis of breast cancer." Expert Systems with Applications. 37 (4), pp. 3344-3351. https://doi.org/10.1016/j.eswa.2009.10.016