Computed tomography (CT) is one of the most common imaging modalities used in industrial, healthcare, and security settings. During a CT scan, a narrow beam of x-rays is used to produce signals that are processed by a computer to generate cross-sectional images of a part of the human body, such as the lungs of a suspected COVID-19 patient or a patient in recovery needing long-term rehabilitation. With multiple tomographic images, they can be digitally stacked together to form a 3D image. However, when the number of image projection is small, streak artifacts can pollute the reconstructed image. Correcting the images takes more time to process and may not improve the image presented to the healthcare provider for diagnosis.

To solve these issues, LLNL has developed an innovative software package for CT reconstruction called Livermore Tomography Tools (LTT). LTT implements advanced algorithms to build 3D images of an object using just a few views, compared to the thousands of views that are typically necessary for traditional CT scans. LTT is platform independent and capable of processing data on one or more graphical processing units (GPUs) or other hardware accelerators. It can be used as a stand-alone application, accessed as a library from existing applications, or used with a separate graphical user interface. LTT provides quantitively accurate results independent of the system, and its flexibility allows data to be processed from any CT geometry, independent of the computing platform. By reducing the time needed to properly reconstruct a 3D image, LTT can increase throughput for medical screening using CT scanning and may significantly reduce the number of scans required—which further reduces both patients’ exposure to radiation and the operational costs and time demands on healthcare providers.

US patents pending, LLNS copyrights asserted