An accurate and fully automatic method for detecting and quantifying emphysema in CT-images is presented. The method is based on an image preprocessing step followed by a neural network classifier trained to separate true em-physema from artifacts. The proposed approach is shown to be superior to an established method when applied on real patient data.
INTRODUCTION The aim of this study was to assess the volume of gas being poorly ventilated or non-ventilated within the lungs of patients treated with mechanical ventilation and suffering from acute respiratory distress syndrome (ARDS). METHODS A prospective, descriptive study was performed of 25 sedated and paralysed ARDS patients, mechanically… (More)