Segmented algorithm for three-dimensional reconstruction in linear scan geometry

Background: Computer tomography is recognized as one of the most powerful methods for diagnosis, and monitoring of a wide range of diseases. It provides the ability to obtain detailed information about the internal structure of organs and bones. Despite the success of computed tomography in areas such as three-dimensional mammography or lung radiography, it has not achieved the same level of widespread as, for example, magnetic resonance imaging, even if CT offers greater accuracy. This is primarily due to safety limitations on the permissible number of examinations due to the harmfulness of X-ray radiation to the patient. One of the main challenges facing researchers is the need to reduce the time of the entire examination and decrease the radiation exposure to the patient. Overcoming these challenges is crucial for improving the overall efficiency of medical services, optimizing treatment plans, and ultimately enhancing patient outcomes. Thus, addressing these issues through innovative algorithms and methods in computed tomography holds significant potential for revolutionizing medical diagnostics and ensuring continuous progress in modern healthcare. Objectives: The aim of this work was to develop an algorithm for three-dimensional reconstruction that is independent of the conicity of the radiation beam. Therefore, it allows for accurate reconstruction of the entire object with a single rotation of the radiation source around the investigated object. Materials and Methods: The work utilizes methods of integral transforms and computer modeling to solve inverse problems arising in computer tomography. Results: An analytical inversion formula was obtained for three-dimensional computer tomography with linear scan geometry and segmentation. The feasibility of the developed algorithm was verified, and a methodology for research with linear motion of the conical emitter and detectors was developed. Conclusions: The developed algorithm improves the reconstruction of object layers significantly distant from the plane in which the emitter and detector move, compared to existing algorithms.