Stenosis map for volume visualization of constricted tubular structures: Application to coronary artery stenosis. Issue 124 (February 2016)

• Record Type: Journal Article
• Authors: Yun, Jihye; Kim, Yeo Koon; Chun, Eun Ju; Shin, Yeong-Gil; Lee, Jeongjin; Kim, Bohyoung
• Is Part Of: Computer methods and programs in biomedicine. Issue 124(2016)
• Page Start: 76
• Page End: 90
• Publication Date: 2016-02
• Subjects: Volume rendering -- Transfer function -- Tubular structure -- Constriction -- Coronary artery stenosis; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2015.10.019
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: A new 3D spatial field for visualizing constricted tubular structures is proposed. Constrictions are quantified by new measures using the localized structure analysis. A new transfer function maps the degree of constriction to color and opacity. Our method provides intuitive adjustment of the visual appearance of constrictions. Our method can be applied to various constrictions with relevant parameters. Abstract: Although direct volume rendering (DVR) has become a commodity, effective rendering of interesting features is still a challenge. In one of active DVR application fields, the medicine, radiologists have used DVR for the diagnosis of lesions or diseases that should be visualized distinguishably from other surrounding anatomical structures. One of most frequent and important radiologic tasks is the detection of lesions, usually constrictions, in complex tubular structures. In this paper, we propose a 3D spatial field for the effective visualization of constricted tubular structures, called as a stenosis map which stores the degree of constriction at each voxel. Constrictions within tubular structures are quantified by using newly proposed measures (i.e. line similarity measure and constriction measure) based on the localized structure analysis, and classified with a proposed transfer function mapping the degree of constriction to color and opacity. We show the application results of our method to the visualization of coronary artery stenoses. We present performance evaluations using twenty eight clinical datasets, demonstrating high accuracy and efficacy of our proposed method. The ability of our method to saliently visualize the constrictions within tubular structures and interactively adjust the visual appearance of the constrictions proves to deliver a substantial aid in radiologic practice.