Optimization and Application Analysis of Phase Correction Method Based on Improved Image Registration in Ultrasonic Image Detection

被引:0
作者
Lu, Nannan [1 ]
Shu, Hongyan [1 ]
机构
[1] Huangshi Matern & Childrens Hlth Hosp, Dept Ultrasound Med, Huangshi, Hubei, Peoples R China
关键词
application optimization; health care; image detection; image registration; phase correction; ultrasound images; VESSEL-BASED REGISTRATION; INTRAOPERATIVE ULTRASOUND; 2D ULTRASOUND; 3D; COMPRESSION; TOMOGRAPHY; VALIDATION; GUIDANCE;
D O I
10.1002/ima.23185
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In order to prevent and detect a wide range of disorders, including those of the brain, thoracic, digestive, urogenital, and cardiovascular systems, ultrasound technology is essential for assessing physiological data and tissue morphology. Its capacity to deliver real-time, high-frequency scans makes it a handy and non-invasive diagnostic tool. However, issues like patient movements and probe jitter from human error can provide a large amount of interference, resulting in inaccurate test findings. Techniques for image registration can assist in locating and eliminating unwanted interference while maintaining crucial data. Even though there has been research on improving these techniques in Matlab, there are no specialized systems for interference removal, and the procedure is still time-consuming, particularly when working with huge quantities of ultrasound images. The phase correlation technique, which converts images into the frequency domain and makes noise suppression easier, is one of the most efficient algorithms now in use since it can tolerate noise with resilience. Nevertheless, little research has been done on using this technique to identify displacement in blood vessel wall ultrasound images. To address these gaps, this work presents an image registration system that uses the phase correlation algorithm. The system provides rotation, zoom registration, picture translation, and displacement detection of the vessel wall in addition to interference removal. Furthermore, batch processing is included to increase the effectiveness of registering multiple ultrasound pictures. Through efficient interference management and streamlined registration, this method offers a workable way to improve the precision and efficacy of ultrasonic diagnostics.
引用
收藏
页数:12
相关论文
共 44 条
  • [21] Registering Preprocedure Volumetric Images With Intraprocedure 3-D Ultrasound Using an Ultrasound Imaging Model
    King, A. P.
    Rhode, K. S.
    Ma, Y.
    Yao, C.
    Jansen, C.
    Razavi, R.
    Penney, G. P.
    [J]. IEEE TRANSACTIONS ON MEDICAL IMAGING, 2010, 29 (03) : 924 - 937
  • [22] Sound speed estimation using automatic ultrasound image registration
    Krücker, JF
    Fowlkes, JB
    Carson, PL
    [J]. IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL, 2004, 51 (09) : 1095 - 1106
  • [23] 3D spatial compounding of ultrasound images using image-based nonrigid registration
    Krücker, JF
    Meyer, CR
    LeCarpentier, GL
    Fowlkes, JB
    Carson, PL
    [J]. ULTRASOUND IN MEDICINE AND BIOLOGY, 2000, 26 (09) : 1475 - 1488
  • [24] An overview of deep learning methods for image registration with focus on feature-based approaches
    Kuppala, Kavitha
    Banda, Sandhya
    Barige, Thirumala Rao
    [J]. INTERNATIONAL JOURNAL OF IMAGE AND DATA FUSION, 2020, 11 (02) : 113 - 135
  • [25] Multi-modal registration of speckle-tracked freehand 3D ultrasound to CT in the lumbar spine
    Lang, Andrew
    Mousavi, Parvin
    Gill, Sean
    Fichtinger, Gabor
    Abolmaesumi, Purang
    [J]. MEDICAL IMAGE ANALYSIS, 2012, 16 (03) : 675 - 686
  • [26] Motion corrected free-breathing Delayed-enhancement imaging of myocardial infarction using nonrigid registration
    Ledesma-Carbayo, Maria J.
    Kellman, Peter
    Arai, Andrew E.
    McVeigh, Elliot R.
    [J]. JOURNAL OF MAGNETIC RESONANCE IMAGING, 2007, 26 (01) : 184 - 190
  • [27] Comparison between MR and CT imaging used to correct for skull-induced phase aberrations during transcranial focused ultrasound
    Leung, Steven A.
    Moore, David
    Gilbo, Yekaterina
    Snell, John
    Webb, Taylor D.
    Meyer, Craig H.
    Miller, G. Wilson
    Ghanouni, Pejman
    Pauly, Kim Butts
    [J]. SCIENTIFIC REPORTS, 2022, 12 (01)
  • [28] An improved image registration and fusion algorithm
    Li, Dan
    Chen, Lei
    Bao, Wenzheng
    Sun, Jinping
    Ding, Bin
    Li, Zilong
    [J]. WIRELESS NETWORKS, 2021, 27 (05) : 3597 - 3611
  • [29] Motion correction of in vivo three-dimensional optical coherence tomography of human skin using a fiducial marker
    Liew, Yih Miin
    McLaughlin, Robert A.
    Wood, Fiona M.
    Sampson, David D.
    [J]. BIOMEDICAL OPTICS EXPRESS, 2012, 3 (08): : 1774 - 1786
  • [30] Lucas BD, 1981, Proceedings of the 7th International Joint Conference on Artificial Intelligence, P674