Lung Movement Determination in Temporal Sequences of MR Images Using Hough Transform and Interval Arithmetics

Abstract

Since the lung is an organ whose real movement has never been seen, as it is totally dependent on the rib cage and collapses without them, the objective of the present work is to develop a method to study its movement. The visualization of the lung in motion is an actual topic of research in medicine. Computerized Tomography (CT) can obtain spatiotemporal images of the heart by synchronizing with electrocardiographic waves. The field of view (FOV) of the heart is small when compared to the lung's FOV. The lung's movement is not periodic and it is susceptible to variations in the degree of respiration. Compared to CT, Magnetic Resonance (MR) imaging involves longer acquisition times and it is preferable because they do not involve radiation. The breathing is associated to a standard respiratory function, and through 2D image processing, edge detection, Hough transform and interval arithmetics, respiratory functions are obtained and, consequently, the position of the points in time are estimated. A standard respiratory function must be provided as input to the modified Hough transform. The Hough transform uses a discrete quantization space, implemented as an accumulator matrix. An improved Hough transform is proposed by using interval arithmetics in the accumulation phase of the algorithm. The discreteness of the quantization space is considered in the algorithm, and its consequences are minimized. This work showed more consistent results when compared to previous approaches.