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Combining SOM based clustering and MGS for classification of suspicious areas within digital mammograms

หน่วยงาน Central Queensland University, Australia

รายละเอียด

ชื่อเรื่อง : Combining SOM based clustering and MGS for classification of suspicious areas within digital mammograms
นักวิจัย : McLeod, Peter. , Verma, Brijesh. , Panchal, Rinku.
คำค้น : Breast , Not a CQU Research Flagship , 700102 Application tools and system utilities , 280207 Pattern Recognition , 280212 Neural Networks, Genetic Alogrithms and Fuzzy Logic , 280208 Computer Vision , Pattern recognition systems. , Neural networks (Computer science) , Application software. , Clustering algorithms -- Neural network based classifiers -- Digital mammography -- Pattern recognition
หน่วยงาน : Central Queensland University, Australia
ผู้ร่วมงาน : -
ปีพิมพ์ : 2550
อ้างอิง : , http://hdl.cqu.edu.au/10018/12529 , http://hdl.cqu.edu.au/10018/12529 , http://dx.doi.org/10.1109/ISSNIP.2007.4496879
ที่มา : McLeod, P, Verma, B & Panchal, R 2007, 'Combining SOM based Clustering and MGS for Classification of Suspicious Areas within Digital Mammograms', 2007 International Conference on Intelligent Sensors, Sensor Networks and Information Processing, Melbourne, Australia IEEE, pp. 413-418. http://dx.doi.org/10.1109/ISSNIP.2007.4496879 (viewed 13/5/2008)
ความเชี่ยวชาญ : -
ความสัมพันธ์ : Proceedings of the 2007 International Conference on Intelligent Sensors, Sensor Networks and Information Processing, Melbourne, Australia, 3-6 December 2007 USA : IEEE, 2007. p.413-418 6 pages Refereed 1424415020 , aCQUIRe [electronic resource] : Central Queensland University Institutional Repository.
ขอบเขตของเนื้อหา : -
บทคัดย่อ/คำอธิบาย :

The fusion of clustering and least square based method for the classification of suspicious areas into benign and malignant classes in digital mammograms was investigated in our previous paper which showed some promising results. This paper extends the investigation by combining a self organising map (SOM) based clustering with modified gram-schmidt (MGS) method. The main focus of the research presented in this paper is to investigate the effect that the assignment of input weights from the SOM clustering algorithm have on the efficiency and accuracy of the neural network classifier. A number of experiments have been conducted on a benchmark database. A comparative analysis with our previous results and other known techniques in the literature is presented in this paper.

บรรณานุกรม :
McLeod, Peter. , Verma, Brijesh. , Panchal, Rinku. . (2550). Combining SOM based clustering and MGS for classification of suspicious areas within digital mammograms.
    กรุงเทพมหานคร : Central Queensland University, Australia.
McLeod, Peter. , Verma, Brijesh. , Panchal, Rinku. . 2550. "Combining SOM based clustering and MGS for classification of suspicious areas within digital mammograms".
    กรุงเทพมหานคร : Central Queensland University, Australia.
McLeod, Peter. , Verma, Brijesh. , Panchal, Rinku. . "Combining SOM based clustering and MGS for classification of suspicious areas within digital mammograms."
    กรุงเทพมหานคร : Central Queensland University, Australia, 2550. Print.
McLeod, Peter. , Verma, Brijesh. , Panchal, Rinku. . Combining SOM based clustering and MGS for classification of suspicious areas within digital mammograms. กรุงเทพมหานคร : Central Queensland University, Australia; 2550.