Application of a respiratory CT sequence's combined histogram to estimate intra-sequence lung's air volume variations
Authors: Ali Sadeghi Naini, Rajni V. Patel and Abbas Samani.
Abstract:
A technique is proposed to segment the lung's air voxels in an image sequence based on a novel image sequence analysis. The concept involves using the image sequence's combined histogram to estimate the lung's air volume and its variations throughout respiratory CT image sequences. Accurate estimation of these parameters is very important in many applications related to lung disease diagnosis and treatment systems (e.g. brachytherapy) where the air volume and its variations are either the variables of interest themselves or are dependent/independent variables. Ex vivo experiments were conducted on porcine left lungs in order to demonstrate the performance of the proposed technique. The proposed method was validated using a breath-hold CT image sequence with known air volumes inside the lung. The results indicate a very good ability of the proposed method for estimating the lung's air volume and its variations in a respiratory image sequence.