G
Giuseppe Coppini
Researcher at National Research Council
Publications - 58
Citations - 987
Giuseppe Coppini is an academic researcher from National Research Council. The author has contributed to research in topics: Image segmentation & Artificial neural network. The author has an hindex of 16, co-authored 57 publications receiving 901 citations.
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Recovery of the 3-D shape of the left ventricle from echocardiographic images
TL;DR: A computational method is reported which allows the fully automated recovery of the three-dimensional shape of the cardiac left ventricle from a reduced set of apical echo views, and the efficiency of such an implementation has been remarkably enhanced through a learning algorithm which embeds specific knowledge about theshape of the left Ventricle in the network.
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Detection of single and clustered microcalcifications in mammograms using fractals models and neural networks.
TL;DR: Results indicate that fractal models provide an adequate framework for medical image processing; consequently high correct classification rates are achieved.
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Neural networks for computer-aided diagnosis: detection of lung nodules in chest radiograms
TL;DR: A neural-network-based system for the computer aided detection of lung nodules in chest radiograms based on multiscale processing and artificial neural networks of the feedforward type is described, which support the undertaking of system validation in clinical settings.
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Heart Rate and Heart Rate Variability From Single-Channel Video and ICA Integration of Multiple Signals
TL;DR: The results support the conclusion that proposed ICA pre-processing can effectively improve the HR and HRV assessment from iPPG.
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A smart mirror to promote a healthy lifestyle
Sara Colantonio,Giuseppe Coppini,Danila Germanese,Daniela Giorgi,Massimo Magrini,Paolo Marraccini,Massimo Martinelli,Maria Aurora Morales,Maria Antonietta Pascali,Giovanni Raccichini,Marco Righi,Ovidio Salvetti +11 more
TL;DR: A novel multisensory device, the Wize Mirror, which is under development in the EU FP7 Project SEMEOTICONS, detects and monitors over time semeiotic face signs related to cardio-metabolic risk, and encourages users to reduce their risk by improving their lifestyle.