Detecting Lung Cancer Symptoms with Analogic CNN Algorithms Based on a Constrained Diffusion Template

Satoshi HIRAKAWA  Csaba REKECZKY  Yoshifumi NISHIO  Akio USHIDA  Tamas ROSKA  Junji UENO  Ishtiaq KASEM  Hiromu NISHITANI  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E80-A   No.7   pp.1340-1344
Publication Date: 1997/07/25
Online ISSN: 
Print ISSN: 0916-8508
Type of Manuscript: LETTER
Category: Nonlinear Problems
cellular neural networks,  image processing,  diffusion,  X-ray films,  

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In this article, a new type of diffusion template and an analogic CNN algorithm using this diffusion template for detecting some lung cancer symptoms in X-ray films are proposed. The performance of the diffusion template is investigated and our CNN algorithm is verified to detect some key lung cancer symptoms, successfully.