A novel soft cluster neural network for the classification of suspicious areas in digital mammograms
Article
Article Title | A novel soft cluster neural network for the classification of suspicious areas in digital mammograms |
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ERA Journal ID | 4503 |
Article Category | Article |
Authors | Verma, Brijesh (Author), McLeod, Peter (Author) and Klevansky, Alan (Author) |
Journal Title | Pattern Recognition |
Journal Citation | 42 (9), pp. 1845-1852 |
Number of Pages | 8 |
Year | 2009 |
Place of Publication | Netherlands |
ISSN | 0031-3203 |
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. |
Keywords | pattern classification; neural networks; clustering algorithms |
ANZSRC Field of Research 2020 | 469999. 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 Affiliations | Central Queensland University |
Department of Health, Queensland | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q2w46/a-novel-soft-cluster-neural-network-for-the-classification-of-suspicious-areas-in-digital-mammograms
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