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 as lungs or heart, distortions and blur arise as a result of the organ motion during breathing and blood supply. Consequently, the image quality declines, despite the use of expensive high resolution devices. Hence, such devices are not exploited fully. There is a need to overcome the problem in alternative ways. Such as alternative is image restoration. 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 reconstruction 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 reconstruction of an image, according to the OTF of the lung motion, which is in several directions simultaneously. One way of handling the 3D 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. As 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.