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Automatic Segmentation of Left Ventricle from Cardiac MRI via Deep Learning and Region Constrained Dynamic Programming
Publication date: Available online 16 February 2019Source: NeurocomputingAuthor(s): Hu Huaifei, Ning Pan, Jiayu Wang, Tailang Yin, Renzhen YeAbstractSegmentation of the left ventricle from cardiac magnetic resonance images (MRI) is an essential step to quantitatively analyze global and regional cardiac function. The aim of this study is to develop a novel and robust algorithm which can improve the accuracy of automatic left ventricle segmentation on short-axis cardiac MRI. The database used in this study are 900 cardiac MRI cases from Hubei Cancer Hospital. Three key techniques are developed in this segmentation algorithm:...
Source: Neurocomputing - February 16, 2019 Category: Neuroscience Source Type: research

A machine learning approach to measure and monitor physical activity in children
Publication date: 8 March 2017 Source:Neurocomputing, Volume 228 Author(s): Paul Fergus, Abir J. Hussain, John Hearty, Stuart Fairclough, Lynne Boddy, Kelly Mackintosh, Gareth Stratton, Nicky Ridgers, Dhiya Al-Jumeily, Ahmed J. Aljaaf, Jenet Lunn The growing trend of obesity and overweight worldwide has reached epidemic proportions with one third of the global population now considered obese. This is having a significant medical impact on children and adults who are at risk of developing osteoarthritis, coronary heart disease and stroke, type 2 diabetes, cancers, respiratory problems, and non-alcoholic fatty liver disease...
Source: Neurocomputing - January 16, 2017 Category: Neuroscience Source Type: research