A NEURAL NETWORK BASED SUMMARIZING METHOD OF PERIODIC IMAGE SEQUENCES

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A NEURAL NETWORK BASED SUMMARIZING METHOD OF PERIODIC IMAGE SEQUENCES Powered By Docstoc
					             A NEURAL NETWORK BASED
     SUMMARIZING METHOD OF PERIODIC
                       IMAGE SEQUENCES
  Mohamed Berkane∗ Patrick Clarysse, Josiane Yankam Njiwa, Yue Min Zhu,
                 ,
                           Isabelle E. Magnin†




Abstract: This work relates to the study of periodic events such as the ones
that can be observed in
				
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Description: This work relates to the study of periodic events such as the ones that can be observed in biomedicine. Currently, biological processes exhibiting a periodic behaviour can be observed through the continuous recording of signals or images. Due to various reasons, cycle duration may slightly vary over time. For further analysis, it is important to be able to extract meaningful information from the mass of acquired data. This paper presents a new neural network based method for the extraction of a summarized cycle from long and massive cycle recordings. Its concept is simple and it could be naturally implemented on a hardware architecture to speed up the process. The proposed method is demonstrated on synthetic image sequences of the beating heart, and exploited as a prior in a new approach for the fast reconstruction of Magnetic Resonance Image sequences. [PUBLICATION ABSTRACT]
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