Journal article
An adaptive resource-allocating network for automated detection, segmentation, and classification of breast cancer nuclei topic area: image processing and recognition
IEEE transactions on neural networks, Vol.14(3), pp.680-687
05/01/2003
DOI: 10.1109/TNN.2003.810615
PMID: 18238048
Abstract
This paper presents a unified image analysis approach for automated detection, segmentation, and classification of breast cancer nuclei using a neural network, which learns to cluster shapes and to classify nuclei. The proposed neural network is incrementally grown by creating a new cluster whenever a previously unseen shape is presented. Each hidden node represents a cluster used as a template to provide faster and more accurate nuclei detection and segmentation. Online learning gives the system improved performance with continued use. The effectiveness of the resulting system is demonstrated on a task of cytological image analysis, with classification of individual nuclei used to diagnose the sample. This demonstrates the potential effectiveness of such a system on diagnostic tasks that require the classification of individual cells.
Details
- Title: Subtitle
- An adaptive resource-allocating network for automated detection, segmentation, and classification of breast cancer nuclei topic area: image processing and recognition
- Creators
- Kyoung-Mi Lee - Duksung Women's UniversityW N Street - University of Iowa
- Resource Type
- Journal article
- Publication Details
- IEEE transactions on neural networks, Vol.14(3), pp.680-687
- DOI
- 10.1109/TNN.2003.810615
- PMID
- 18238048
- ISSN
- 1045-9227
- eISSN
- 1941-0093
- Language
- English
- Date published
- 05/01/2003
- Academic Unit
- Bus Admin College; Nursing; Computer Science; Business Analytics
- Record Identifier
- 9984380457902771
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