Algorithm of Pulmonary Vascular Segment and Centerline Extraction

Comput Math Methods Med. 2021 Aug 25;2021:3859386. doi: 10.1155/2021/3859386. eCollection 2021.ABSTRACTBecause pulmonary vascular lesions are harmful to the human body and difficult to detect, computer-assisted diagnosis of pulmonary blood vessels has become the focus and difficulty of the current research. An algorithm of pulmonary vascular segment and centerline extraction which is consistent with the physician's diagnosis process is proposed for the first time. We construct the projection of maximum density, restore the vascular space information, and correct random walk algorithm to satisfy automatic and accurate segmentation of blood vessels. Construct a local 3D model to restrain Hessian matrix when extracting centerline. In order to assist the physician to make a correct diagnosis and verify the effectiveness of the algorithm, we proposed a visual expansion model. According to the 420 high-resolution CT data of lung blood vessels labeled by physicians, the accuracy of segmentation algorithm AOM reached 93%, and the processing speed was 0.05 s/frame, which achieved the clinical application standards.PMID:34484415 | PMC:PMC8413036 | DOI:10.1155/2021/3859386

Source: Computational and Mathematical Methods in Medicine - September 6, 2021 Category: Statistics Authors: Shi Qiu Jie Lian Yan Ding Tao Zhou Ting Liang Source Type: research