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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
Publication Date: 1997/07/25
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.