DocumentCode :
3070956
Title :
Medical image diagnosis of lung cancer by hybrid multi-layered GMDH-type neural network using knowledge base
Author :
Kondo, Tadashi ; Ueno, Junji ; Takao, Shoichiro
Author_Institution :
Grad. Sch. of Health Sci., Univ. of Tokushima, Tokushima, Japan
fYear :
2012
fDate :
1-4 July 2012
Firstpage :
663
Lastpage :
668
Abstract :
A revised Group Method of Data Handling (GMDH)-type neural network algorithm for medical image diagnosis is proposed, and is applied to medical image diagnosis of lung cancer. In this algorithm, the knowledge base for medical image diagnosis are used for organizing the neural network architecture for medical image diagnosis, and the revised GMDH-type neural network algorithm can identify the characteristics of the medical images accurately. The optimum neural network architecture fitting the complexity of the medical images is automatically organized so as to minimize the prediction error criterion defined as Prediction Sum of Squares (PSS), and it is shown that the revised GMDH-type neural network can be easily applied to the medical image diagnosis.
Keywords :
cancer; data handling; knowledge based systems; lung; medical image processing; neural nets; patient diagnosis; PSS; group method of data handling; hybrid multilayered GMDH type neural network; knowledge base; lung cancer; medical image diagnosis; neural network architecture; optimum neural network architecture; prediction sum of squares; Atmospheric modeling; Cancer; Medical diagnostic imaging; GMDH; Medical image diagnosis; Neural network; knowledge base; self-organization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Complex Medical Engineering (CME), 2012 ICME International Conference on
Conference_Location :
Kobe
Print_ISBN :
978-1-4673-1617-0
Type :
conf
DOI :
10.1109/ICCME.2012.6275721
Filename :
6275721
Link To Document :
بازگشت