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Classification of breast abnormalities in digital mammograms using image and BI-RADS features in conjunction with neural network

หน่วยงาน Central Queensland University, Australia

รายละเอียด

ชื่อเรื่อง : Classification of breast abnormalities in digital mammograms using image and BI-RADS features in conjunction with neural network
นักวิจัย : Panchal, R. M. , Verma, Brijesh.
คำค้น : 700102 Application tools and system utilities. , 280212 Neural Networks, Genetic Algorithms and Fuzzy Logic. , TBA. , 890202 Application Tools and System Utilities. , 8902 Computer Software and Services. , 89 Information and Communication Services. , 080108 Neural, Evolutionary and Fuzzy Computation. , 0801 Artificial Intelligence and Image Processing. , 08 Information and Computing Sciences. , Breast , Neural networks (Computer science)
หน่วยงาน : Central Queensland University, Australia
ผู้ร่วมงาน : -
ปีพิมพ์ : 2548
อ้างอิง : http://hdl.cqu.edu.au/10018/23614 , cqu:3695
ที่มา : Panchal, R M & Verma, B 2005, 'Classification of breast abnormalities in digital mammograms using image and bi-rads features in conjunction with neural network', paper presented at IEEE International Joint Conference on Neural Networks., Montreal. http://dx.doi.org/10.1109/IJCNN.2005.1556293
ความเชี่ยวชาญ : -
ความสัมพันธ์ : Proceedings of the IEEE International Joint Conference on Neural Networks. New Jersey. : IEEE, 2005. p. 2487-2492 6 pages Refereed 0780390490 , ACQUIRE [electronic resource] : Central Queensland University Institutional Repository.
ขอบเขตของเนื้อหา : -
บทคัดย่อ/คำอธิบาย :

This paper investigates the significance of combining grey-level based image features and BI-RADS lesion descriptors along with patient age and a subtlety value (radiologists' interpretation) for the reliable classification of calcification and mass type breast abnormalities into malignant and benign classes. Three sets of experiments using grey-level based image features, BI-RADS features and combined features were conducted on DDSIM benchmark database. The classification rate 91% on mass dataset and 74% on calcification dataset was obtained when both types of features combined together.

บรรณานุกรม :
Panchal, R. M. , Verma, Brijesh. . (2548). Classification of breast abnormalities in digital mammograms using image and BI-RADS features in conjunction with neural network.
    กรุงเทพมหานคร : Central Queensland University, Australia.
Panchal, R. M. , Verma, Brijesh. . 2548. "Classification of breast abnormalities in digital mammograms using image and BI-RADS features in conjunction with neural network".
    กรุงเทพมหานคร : Central Queensland University, Australia.
Panchal, R. M. , Verma, Brijesh. . "Classification of breast abnormalities in digital mammograms using image and BI-RADS features in conjunction with neural network."
    กรุงเทพมหานคร : Central Queensland University, Australia, 2548. Print.
Panchal, R. M. , Verma, Brijesh. . Classification of breast abnormalities in digital mammograms using image and BI-RADS features in conjunction with neural network. กรุงเทพมหานคร : Central Queensland University, Australia; 2548.