Acute Respiratory Distress Syndrome (ARDS) has a mortality estimated at 50%. Its management relies on mechanical ventilation to support the respiration. However, it is estimated that 25% of the deaths might be avoided if the parameter setting of the ventilation is better adapted to the patients. A new medical research study, started by the team of Réanimation Médicale, Hôpital de la Croix-Rousse, Lyon, France, using an animal model (piglets) with ARDS induced, aims to analyze the response of the lung to mechanical ventilation. The study uses computed tomography (CT) images to quantify the aeration. This task requires the delimitation of the lung in the images. However, in the case of ARDS, this delimitation is hindered by the reduced contrast between the lung and the surrounding structures. Traditional lung segmentation methods are not suited for those images. In this work, a method for the quantification of aeration in CT images for the medical study is presented. The method takes advantage of the acquisition protocol of the medical study. The protocol has two trials, each one uses a series of ventilation conditions (combination of pressure and volume). For each ventilation condition an image is acquired. First, a registration process is started. Beginning with the trial of decreasing pressure and constant volume (Vk), the image with the highest pressure I (Pmax,Vk) is registered to the image with the next lower pressure I(Pmax−1,Vk). Then, the process continues in a cascade way, registering I(Pi,Vk) to I(Pi−1,Vk) until the last pressure I(Pmin,Vk) is reached. The same process is used in the increasing volume and constant pressure (Pr) trial until the maximum volume image I(Pr,Vmax) is reached. The starting image is taken from the precedent trial as the one that has the closest pressure to Pr. Once all the images are registered, the result of an automatic lung segmentation performed on the image I(Pmax, Vk) is transformed to the other images using the deformation fields found in the registration process. Finally, the aeration in each image is quantified using the lung segmentation to delimit the quantification. Results over 16 pigs (502 images) were visually inspected by an expert. The segmentations were found consistent within the ventilation conditions. The quantification showed an expected tendency with respect to the behavior of the aeration in the different ventilation conditions. The proposed method quantifies the aeration in different mechanical ventilation conditions in an animal model with ARDS induced. The results are visually consistent and satisfactory.