Development and clinical application of a high‐performance medical static computed tomography system

Abstract Purpose Conventional helical computed tomography (CT) is limited by constraints related to centripetal acceleration, with current rotation speeds nearing the boundaries of engineering feasibility. This study addresses these challenges by proposing a novel CT system design Methods This study introduces an innovative multi‐source static CT architecture that employs an array‐based, fully integrated x‐ray source paired with a photon stream detector. This system utilizes a complete circular configuration and implements a sequential exposure strategy for each source, thereby eliminating the need for mechanical rotation typical of traditional helical CT. Leveraging the compact integration of the x‐ray source and the fine pixel structure of the detector, we developed a compressed‐sensing iterative reconstruction algorithm based on the bilateral extended Feldkamp‐Davis‐Kress (bixFDK), referred to as “iVision” reconstruction. In addition, a software‐based scatter correction algorithm was implemented. These enhancements collectively improve system performance by significantly boosting spatial resolution. Results The multi‐source static CT system met all key regulatory standards for performance indicators, including image noise, uniformity, measurement accuracy, spatial resolution, and density resolution. Notably, the system achieved a spatial resolution of up to 25 LP/cm@MTF = 10%, positioning it at the forefront of ultra‐high‐resolution CT imaging. In volunteer clinical scans, the system consistently delivered sharper images of anatomical regions such as the head, chest, abdomen, and musculoskeletal structures, outperforming conventional helical CT, particularly in detailed visualization of bones and joints, pulmonary tissues, and internal organs. Conclusions Based on the above results and analyses, this multi‐source static CT system achieves diagnostic‐quality imaging, aligning with clinical practice standards. It excels in capturing fine anatomical detail and detecting critical pathological features. Its high‐resolution capability also supports precise diagnoses of hip fractures and facilitates detailed trabecular bone assessment, thus improving overall diagnostic accuracy.