Medical image restoration of dynamic lungs using optical transfer function of lung motion.

When carrying out medical imaging based on detection of isotopic radiation levels of internal organs such a lungs or heart, distortions, and blur arise as a result of the organ motion during breathing and blood supply. Consequently, image quality declines, despite the use of expensive high resolution devices and, such devices are not exploited fully. A method with which to overcome the problem is image restoration. Previously, we suggested and developed a method for calculating numerically the optical transfer function (OTF) for any type of image motion. The purpose of this research is restoration of original isotope images (of the lungs) by restoration methods that depend on the OTF of the real time relative motion between the object and the imaging system. This research uses different algorithms for the restoration of an image, according to the OTF of the lung motion, which is in several directions simultaneously. One way of handling the three-dimensional movement is to decompose the image into several portions, to restore each portion according to its motion characteristics, and then to combine all the image portions back into a single image. An additional complication is that the image was recorded at different angles. The application of this research is in medical systems requiring high resolution imaging. The main advantage of this approach is its low cost versus conventional approaches.