Registration of photoacoustic tomography vascular images: Comparison and analysis of automatic registration approaches

作者全名："Yu, Qinran; Liao, Yixing; Liu, Kecen; He, Zhengyan; Zhao, Yuan; Li, Faqi; Shan, Tianqi"

作者地址："[Yu, Qinran; Liao, Yixing; Liu, Kecen; He, Zhengyan; Zhao, Yuan; Li, Faqi; Shan, Tianqi] Chongqing Med Univ, Coll Biomed Engn, State Key Lab Ultrasound Med & Engn, Chongqing, Peoples R China"

通信作者："Zhao, Y; Li, FQ; Shan, TQ (通讯作者)，Chongqing Med Univ, Coll Biomed Engn, State Key Lab Ultrasound Med & Engn, Chongqing, Peoples R China."

来源：FRONTIERS IN PHYSICS

ESI学科分类：PHYSICS

WOS号：WOS:000894493200001

JCR分区：Q2

影响因子：3.1

年份：2022

卷号：10

期号：　

开始页：　

结束页：　

文献类型：Article

关键词：image registration; intensity-based registration; photoacoustic tomography; visual perception; photoacoustic imaging; vascular

摘要："Image registration is crucial in the clinical application of photoacoustic tomography (PAT) for vascular growth monitoring. Aiming to find an optimized registration scheme for PAT vascular images acquired at different times and with varying imaging conditions, we compared and analyzed different commonly used intensity-based and feature-based automatic registration schemes. To further improve the registration performance, we proposed a new scheme that combines phase correlation with these commonly used intensity-based registration methods and compared their performances. The objective evaluation measures: peak signal-to-noise ratio (PSNR), structural similarity index metric (SSIM), root mean square error (RMSE), and quantitative visual perception (jump percentage P), as well as subjective evaluation using mean opinion score (MOS), were combined to evaluate the registration performance. Results show that the feature-based approaches in this study were not suitable for PAT image registration. And by adding phase correlation as rough registration, the overall registration performance was improved significantly. Among these methods, the proposed scheme of phase correlation combined with mean square error (MSE) similarity measure and regular-step-gradient-descent optimizer provides the best visual effect, accuracy, and efficiency in PAT vascular image registration."

基金机构："Youth fund project of National Natural Science Foundation of China [62101083, 62201103]; China Postdoctoral Science Foundation [2020M683260]; Natural Science Foundation of Chongqing, China [cstc2021jcyj-msxmX0104, cstc2021jcyj-msxmX0739]"

基金资助正文："This research was supported by the Youth fund project of National Natural Science Foundation of China under grant 62201103, 62101083; Project funded by China Postdoctoral Science Foundation 2020M683260; and Natural Science Foundation of Chongqing, China under grant cstc2021jcyj-msxmX0739, cstc2021jcyj-msxmX0104."