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Multicluster class-based classification for the diagnosis of suspicious areas in digital mammograms

หน่วยงาน Central Queensland University, Australia

รายละเอียด

ชื่อเรื่อง : Multicluster class-based classification for the diagnosis of suspicious areas in digital mammograms
นักวิจัย : Verma, Brijesh.
คำค้น : Breast , Applied research. , 890202 Application Tools and System Utilities. , 920203 Diagnostic Methods. , 080108 Neural, Evolutionary and Fuzzy Computation. , 080109 Pattern Recognition and Data Mining. , Breast , Pattern perception. , Diagnostic imaging. , Neural networks (Computer science) , Clustering -- Classifiers -- Neural networks -- Digital mammography
หน่วยงาน : Central Queensland University, Australia
ผู้ร่วมงาน : -
ปีพิมพ์ : 2552
อ้างอิง : http://hdl.cqu.edu.au/10018/43939
ที่มา : Verma, B 2009, 'Multi-cluster Class based Classification for the Diagnosis of Suspicious Areas in Digital Mammograms', in Pham, Tuan (eds),Computational Biology: Issues and Applications in Oncology - Series Title: Applied Bioinformatics and Biostatistics in Cancer Research , Springer, New York, USA.
ความเชี่ยวชาญ : -
ความสัมพันธ์ : Computational biology : issues and applications in oncology / Tuan Pham, editor. New York, USA : Springer, 2009. Chapter 5, p. 113-124 309 pages 12 chapters 9781441908100 , ACQUIRE [electronic resource] : Central Queensland University Institutional Repository.
ขอบเขตของเนื้อหา : -
บทคัดย่อ/คำอธิบาย :

This book chapter presents a multi-cluster class based classification approach for the classification of suspicious areas extracted from digital mammograms into benign and malignant classes. The approach creates multiple clusters and selects strong clusters for each class. The created strong clusters are used to form subclasses within benign and malignant classes and training of a classifier. The creation of strong multiple clusters during the classification process can improve the accuracy of the classification system. The experiments using multi-cluster class based approach and a standard classifier with a single cluster per class have been conducted on a benchmark database of digital mammograms. The results have shown that the multi-cluster class based approach makes a significant impact on improving the classification accuracy.

บรรณานุกรม :
Verma, Brijesh. . (2552). Multicluster class-based classification for the diagnosis of suspicious areas in digital mammograms.
    กรุงเทพมหานคร : Central Queensland University, Australia.
Verma, Brijesh. . 2552. "Multicluster class-based classification for the diagnosis of suspicious areas in digital mammograms".
    กรุงเทพมหานคร : Central Queensland University, Australia.
Verma, Brijesh. . "Multicluster class-based classification for the diagnosis of suspicious areas in digital mammograms."
    กรุงเทพมหานคร : Central Queensland University, Australia, 2552. Print.
Verma, Brijesh. . Multicluster class-based classification for the diagnosis of suspicious areas in digital mammograms. กรุงเทพมหานคร : Central Queensland University, Australia; 2552.